Homework 6

Part 1

Write code to create a random data set with a normal distribution and defined standard deviation, sample size, and mean.

response_1 <- rnorm(n=100, mean=15, sd=2)
print(response_1)

##   [1] 12.75221 16.97134 11.93858 15.43975 18.16369 14.98714 17.66722 17.88478
##   [9] 18.70059 18.43300 14.68135 14.15171 17.79062 15.90260 17.29890 16.60597
##  [17] 13.78165 18.25001 12.47342 12.95815 12.78681 19.49908 13.63907 14.32157
##  [25] 13.33003 12.54924 16.55099 13.31660 13.98828 15.22059 18.82432 11.58368
##  [33] 11.43019 12.91494 11.69414 12.68359 12.11656 13.53336 13.13509 14.55093
##  [41] 14.52722 16.35755 13.17503 14.58819 13.52473 15.48732 15.66154 16.06228
##  [49] 11.20823 15.43031 14.96983 12.30922 12.55078 14.69011 11.01355 15.13167
##  [57] 16.83424 14.26499 16.87356 13.72272 16.19120 14.43165 15.20739 13.39218
##  [65] 13.82927 12.20703 11.01454 15.39590 14.21469 13.84379 15.86127 14.04684
##  [73] 15.40675 17.25987 15.75984 14.87101 20.26480 14.57602 13.57083 15.28048
##  [81] 16.90011 15.82450 13.92557 11.45211 15.95298 17.68226 14.87466 17.78028
##  [89] 16.17980 11.31322 15.33035 13.90324 17.82026 15.25332 14.85957 15.81192
##  [97] 15.24430 16.07864 15.80002 13.65394

response_2 <- rnorm(n=100, mean=30, sd=7)
print(response_2)

##   [1] 35.56657 15.26228 29.10697 31.22651 27.08303 34.44269 29.86253 27.05391
##   [9] 24.50439 41.96130 31.30836 34.38574 29.19776 22.44088 19.44589 36.64647
##  [17] 28.85139 37.36016 26.07276 41.71385 28.38014 39.95773 26.46156 31.72197
##  [25] 26.51280 33.16894 44.22516 36.98551 33.46727 31.52191 36.06449 30.28722
##  [33] 24.48078 32.32184 36.15234 26.20160 22.70306 33.77208 21.80187 22.91352
##  [41] 27.95873 26.81217 39.48527 28.91753 36.61381 28.10556 23.73864 35.61077
##  [49] 29.33773 33.00932 38.03566 26.18545 22.50192 21.39126 25.67083 36.65810
##  [57] 26.31259 33.37477 32.85469 20.96769 14.41171 35.48894 36.50915 39.10973
##  [65] 26.13498 32.40226 38.47815 31.48562 27.01478 36.74334 39.99274 27.21908
##  [73] 31.88131 24.45825 22.81931 31.39251 20.15989 34.22605 29.70458 36.06000
##  [81] 22.38641 23.12985 26.59753 28.03702 17.25609 22.36397 31.16104 31.57977
##  [89] 25.44977 32.77026 29.79645 49.01461 15.09694 41.93027 40.64291 25.18776
##  [97] 32.17061 28.94098 35.74419 40.81714

response <- c(response_1, response_2)

Part 2

Organize these data into a data frame with the appropriate structure.

my_df_1 <- data.frame (X = "control", Y= response_1)
print(my_df_1)

##           X        Y
## 1   control 12.75221
## 2   control 16.97134
## 3   control 11.93858
## 4   control 15.43975
## 5   control 18.16369
## 6   control 14.98714
## 7   control 17.66722
## 8   control 17.88478
## 9   control 18.70059
## 10  control 18.43300
## 11  control 14.68135
## 12  control 14.15171
## 13  control 17.79062
## 14  control 15.90260
## 15  control 17.29890
## 16  control 16.60597
## 17  control 13.78165
## 18  control 18.25001
## 19  control 12.47342
## 20  control 12.95815
## 21  control 12.78681
## 22  control 19.49908
## 23  control 13.63907
## 24  control 14.32157
## 25  control 13.33003
## 26  control 12.54924
## 27  control 16.55099
## 28  control 13.31660
## 29  control 13.98828
## 30  control 15.22059
## 31  control 18.82432
## 32  control 11.58368
## 33  control 11.43019
## 34  control 12.91494
## 35  control 11.69414
## 36  control 12.68359
## 37  control 12.11656
## 38  control 13.53336
## 39  control 13.13509
## 40  control 14.55093
## 41  control 14.52722
## 42  control 16.35755
## 43  control 13.17503
## 44  control 14.58819
## 45  control 13.52473
## 46  control 15.48732
## 47  control 15.66154
## 48  control 16.06228
## 49  control 11.20823
## 50  control 15.43031
## 51  control 14.96983
## 52  control 12.30922
## 53  control 12.55078
## 54  control 14.69011
## 55  control 11.01355
## 56  control 15.13167
## 57  control 16.83424
## 58  control 14.26499
## 59  control 16.87356
## 60  control 13.72272
## 61  control 16.19120
## 62  control 14.43165
## 63  control 15.20739
## 64  control 13.39218
## 65  control 13.82927
## 66  control 12.20703
## 67  control 11.01454
## 68  control 15.39590
## 69  control 14.21469
## 70  control 13.84379
## 71  control 15.86127
## 72  control 14.04684
## 73  control 15.40675
## 74  control 17.25987
## 75  control 15.75984
## 76  control 14.87101
## 77  control 20.26480
## 78  control 14.57602
## 79  control 13.57083
## 80  control 15.28048
## 81  control 16.90011
## 82  control 15.82450
## 83  control 13.92557
## 84  control 11.45211
## 85  control 15.95298
## 86  control 17.68226
## 87  control 14.87466
## 88  control 17.78028
## 89  control 16.17980
## 90  control 11.31322
## 91  control 15.33035
## 92  control 13.90324
## 93  control 17.82026
## 94  control 15.25332
## 95  control 14.85957
## 96  control 15.81192
## 97  control 15.24430
## 98  control 16.07864
## 99  control 15.80002
## 100 control 13.65394

my_df_2 <- data.frame(X = "treatment", Y = response_2)
print(my_df_2)

##             X        Y
## 1   treatment 35.56657
## 2   treatment 15.26228
## 3   treatment 29.10697
## 4   treatment 31.22651
## 5   treatment 27.08303
## 6   treatment 34.44269
## 7   treatment 29.86253
## 8   treatment 27.05391
## 9   treatment 24.50439
## 10  treatment 41.96130
## 11  treatment 31.30836
## 12  treatment 34.38574
## 13  treatment 29.19776
## 14  treatment 22.44088
## 15  treatment 19.44589
## 16  treatment 36.64647
## 17  treatment 28.85139
## 18  treatment 37.36016
## 19  treatment 26.07276
## 20  treatment 41.71385
## 21  treatment 28.38014
## 22  treatment 39.95773
## 23  treatment 26.46156
## 24  treatment 31.72197
## 25  treatment 26.51280
## 26  treatment 33.16894
## 27  treatment 44.22516
## 28  treatment 36.98551
## 29  treatment 33.46727
## 30  treatment 31.52191
## 31  treatment 36.06449
## 32  treatment 30.28722
## 33  treatment 24.48078
## 34  treatment 32.32184
## 35  treatment 36.15234
## 36  treatment 26.20160
## 37  treatment 22.70306
## 38  treatment 33.77208
## 39  treatment 21.80187
## 40  treatment 22.91352
## 41  treatment 27.95873
## 42  treatment 26.81217
## 43  treatment 39.48527
## 44  treatment 28.91753
## 45  treatment 36.61381
## 46  treatment 28.10556
## 47  treatment 23.73864
## 48  treatment 35.61077
## 49  treatment 29.33773
## 50  treatment 33.00932
## 51  treatment 38.03566
## 52  treatment 26.18545
## 53  treatment 22.50192
## 54  treatment 21.39126
## 55  treatment 25.67083
## 56  treatment 36.65810
## 57  treatment 26.31259
## 58  treatment 33.37477
## 59  treatment 32.85469
## 60  treatment 20.96769
## 61  treatment 14.41171
## 62  treatment 35.48894
## 63  treatment 36.50915
## 64  treatment 39.10973
## 65  treatment 26.13498
## 66  treatment 32.40226
## 67  treatment 38.47815
## 68  treatment 31.48562
## 69  treatment 27.01478
## 70  treatment 36.74334
## 71  treatment 39.99274
## 72  treatment 27.21908
## 73  treatment 31.88131
## 74  treatment 24.45825
## 75  treatment 22.81931
## 76  treatment 31.39251
## 77  treatment 20.15989
## 78  treatment 34.22605
## 79  treatment 29.70458
## 80  treatment 36.06000
## 81  treatment 22.38641
## 82  treatment 23.12985
## 83  treatment 26.59753
## 84  treatment 28.03702
## 85  treatment 17.25609
## 86  treatment 22.36397
## 87  treatment 31.16104
## 88  treatment 31.57977
## 89  treatment 25.44977
## 90  treatment 32.77026
## 91  treatment 29.79645
## 92  treatment 49.01461
## 93  treatment 15.09694
## 94  treatment 41.93027
## 95  treatment 40.64291
## 96  treatment 25.18776
## 97  treatment 32.17061
## 98  treatment 28.94098
## 99  treatment 35.74419
## 100 treatment 40.81714

my_df <- rbind(my_df_1, my_df_2)
print(my_df)

##             X        Y
## 1     control 12.75221
## 2     control 16.97134
## 3     control 11.93858
## 4     control 15.43975
## 5     control 18.16369
## 6     control 14.98714
## 7     control 17.66722
## 8     control 17.88478
## 9     control 18.70059
## 10    control 18.43300
## 11    control 14.68135
## 12    control 14.15171
## 13    control 17.79062
## 14    control 15.90260
## 15    control 17.29890
## 16    control 16.60597
## 17    control 13.78165
## 18    control 18.25001
## 19    control 12.47342
## 20    control 12.95815
## 21    control 12.78681
## 22    control 19.49908
## 23    control 13.63907
## 24    control 14.32157
## 25    control 13.33003
## 26    control 12.54924
## 27    control 16.55099
## 28    control 13.31660
## 29    control 13.98828
## 30    control 15.22059
## 31    control 18.82432
## 32    control 11.58368
## 33    control 11.43019
## 34    control 12.91494
## 35    control 11.69414
## 36    control 12.68359
## 37    control 12.11656
## 38    control 13.53336
## 39    control 13.13509
## 40    control 14.55093
## 41    control 14.52722
## 42    control 16.35755
## 43    control 13.17503
## 44    control 14.58819
## 45    control 13.52473
## 46    control 15.48732
## 47    control 15.66154
## 48    control 16.06228
## 49    control 11.20823
## 50    control 15.43031
## 51    control 14.96983
## 52    control 12.30922
## 53    control 12.55078
## 54    control 14.69011
## 55    control 11.01355
## 56    control 15.13167
## 57    control 16.83424
## 58    control 14.26499
## 59    control 16.87356
## 60    control 13.72272
## 61    control 16.19120
## 62    control 14.43165
## 63    control 15.20739
## 64    control 13.39218
## 65    control 13.82927
## 66    control 12.20703
## 67    control 11.01454
## 68    control 15.39590
## 69    control 14.21469
## 70    control 13.84379
## 71    control 15.86127
## 72    control 14.04684
## 73    control 15.40675
## 74    control 17.25987
## 75    control 15.75984
## 76    control 14.87101
## 77    control 20.26480
## 78    control 14.57602
## 79    control 13.57083
## 80    control 15.28048
## 81    control 16.90011
## 82    control 15.82450
## 83    control 13.92557
## 84    control 11.45211
## 85    control 15.95298
## 86    control 17.68226
## 87    control 14.87466
## 88    control 17.78028
## 89    control 16.17980
## 90    control 11.31322
## 91    control 15.33035
## 92    control 13.90324
## 93    control 17.82026
## 94    control 15.25332
## 95    control 14.85957
## 96    control 15.81192
## 97    control 15.24430
## 98    control 16.07864
## 99    control 15.80002
## 100   control 13.65394
## 101 treatment 35.56657
## 102 treatment 15.26228
## 103 treatment 29.10697
## 104 treatment 31.22651
## 105 treatment 27.08303
## 106 treatment 34.44269
## 107 treatment 29.86253
## 108 treatment 27.05391
## 109 treatment 24.50439
## 110 treatment 41.96130
## 111 treatment 31.30836
## 112 treatment 34.38574
## 113 treatment 29.19776
## 114 treatment 22.44088
## 115 treatment 19.44589
## 116 treatment 36.64647
## 117 treatment 28.85139
## 118 treatment 37.36016
## 119 treatment 26.07276
## 120 treatment 41.71385
## 121 treatment 28.38014
## 122 treatment 39.95773
## 123 treatment 26.46156
## 124 treatment 31.72197
## 125 treatment 26.51280
## 126 treatment 33.16894
## 127 treatment 44.22516
## 128 treatment 36.98551
## 129 treatment 33.46727
## 130 treatment 31.52191
## 131 treatment 36.06449
## 132 treatment 30.28722
## 133 treatment 24.48078
## 134 treatment 32.32184
## 135 treatment 36.15234
## 136 treatment 26.20160
## 137 treatment 22.70306
## 138 treatment 33.77208
## 139 treatment 21.80187
## 140 treatment 22.91352
## 141 treatment 27.95873
## 142 treatment 26.81217
## 143 treatment 39.48527
## 144 treatment 28.91753
## 145 treatment 36.61381
## 146 treatment 28.10556
## 147 treatment 23.73864
## 148 treatment 35.61077
## 149 treatment 29.33773
## 150 treatment 33.00932
## 151 treatment 38.03566
## 152 treatment 26.18545
## 153 treatment 22.50192
## 154 treatment 21.39126
## 155 treatment 25.67083
## 156 treatment 36.65810
## 157 treatment 26.31259
## 158 treatment 33.37477
## 159 treatment 32.85469
## 160 treatment 20.96769
## 161 treatment 14.41171
## 162 treatment 35.48894
## 163 treatment 36.50915
## 164 treatment 39.10973
## 165 treatment 26.13498
## 166 treatment 32.40226
## 167 treatment 38.47815
## 168 treatment 31.48562
## 169 treatment 27.01478
## 170 treatment 36.74334
## 171 treatment 39.99274
## 172 treatment 27.21908
## 173 treatment 31.88131
## 174 treatment 24.45825
## 175 treatment 22.81931
## 176 treatment 31.39251
## 177 treatment 20.15989
## 178 treatment 34.22605
## 179 treatment 29.70458
## 180 treatment 36.06000
## 181 treatment 22.38641
## 182 treatment 23.12985
## 183 treatment 26.59753
## 184 treatment 28.03702
## 185 treatment 17.25609
## 186 treatment 22.36397
## 187 treatment 31.16104
## 188 treatment 31.57977
## 189 treatment 25.44977
## 190 treatment 32.77026
## 191 treatment 29.79645
## 192 treatment 49.01461
## 193 treatment 15.09694
## 194 treatment 41.93027
## 195 treatment 40.64291
## 196 treatment 25.18776
## 197 treatment 32.17061
## 198 treatment 28.94098
## 199 treatment 35.74419
## 200 treatment 40.81714

Part 3

Analyze and graph the data.

anova_data <- aov(Y ~ X, data = my_df)
summary <- summary(anova_data)
print(summary[[1]]$`Pr(>F)`)

## [1] 7.755695e-55           NA

library(ggplot2)
plot <- ggplot(my_df, aes(X, Y)) + geom_boxplot() + labs(x="Conditions",y="Responses")
print(plot)

Part 4

For Loop Generation- ADJUSTING SAMPLE SIZE

n <- seq(50, 300, 10)
for (i in 1:length(n)) {
  print(n[i])
}

## [1] 50
## [1] 60
## [1] 70
## [1] 80
## [1] 90
## [1] 100
## [1] 110
## [1] 120
## [1] 130
## [1] 140
## [1] 150
## [1] 160
## [1] 170
## [1] 180
## [1] 190
## [1] 200
## [1] 210
## [1] 220
## [1] 230
## [1] 240
## [1] 250
## [1] 260
## [1] 270
## [1] 280
## [1] 290
## [1] 300

response_1 <- rnorm(n=n[i], mean=15, sd=2)
print(response_1)

##   [1] 13.524850 16.162169 16.657575 16.137966 14.581420 13.858991 19.045828
##   [8] 15.545089 16.123825 14.299803 17.002045 15.759880 13.072970 15.938578
##  [15] 17.360188 14.209815 16.093269 12.860212  9.350368 12.861384 14.528101
##  [22] 10.982822 15.481775 13.808889 13.448322 14.072885 12.585229 12.172660
##  [29] 14.556322 17.678359 14.655668 15.725132 14.433328 15.558840 11.653116
##  [36] 17.674471 16.571423 13.002206 16.538782 15.968290 17.153381 14.505149
##  [43] 12.856031 14.059467 15.986151 18.383773 13.814169 14.831214 16.102674
##  [50] 19.286194 15.697546 13.068484 18.594191 16.735174 17.657626 15.113586
##  [57] 15.803128 14.408149 13.113259 13.961630 13.782922 13.897541 17.905224
##  [64] 19.509321 14.738527 15.362901 16.795910 16.732088 13.801756 13.211352
##  [71] 15.071874 19.484375 18.075572 15.875530 14.241704 13.654567 16.581585
##  [78] 17.743569 14.367956 12.141891 12.153958 18.626676 16.495305 16.645334
##  [85] 11.851035 16.081154 18.318775 14.754154 16.868047 16.724617 14.758559
##  [92]  9.475854 17.441484 13.897368 14.910525 15.814793 14.640143 15.078015
##  [99] 15.213515 15.706322 15.247965 13.146854 11.364270 16.077684 17.381601
## [106] 15.414467 11.776056 14.750541 15.029076 16.208454 15.346990 15.673430
## [113] 12.859934 18.057441 15.170795 12.473666 12.641136 15.331539 13.158327
## [120] 15.958656 12.417232 16.215906 12.870563 12.593260 16.027780 13.462400
## [127] 11.568257 17.962238 15.361641 11.963316 13.921920 14.612572 11.135482
## [134] 14.291027 15.815209 16.685966 14.676643 17.567754 13.381781 17.090650
## [141] 15.350637 16.125473 16.462265 14.320864 15.741398 14.697217 15.982210
## [148] 14.956769 16.058912 14.840666 12.397339 15.608417 17.699649 10.813945
## [155] 14.282665 13.553862 12.759383 16.478448 18.840037 14.934314 19.711098
## [162] 16.524151 11.108402 11.926968 17.637653 14.013088 13.009632 17.991936
## [169] 10.399573 12.858779 17.070789 19.007162 15.943364 14.028840 14.519849
## [176] 12.383627 15.536302 17.772054 11.272484 16.663617 14.090546 11.269606
## [183] 15.680611 10.637629 17.419836 11.937020 12.773752 14.118267 15.851570
## [190] 12.293068 18.317905 13.546393 13.265006 14.940806 13.824269 14.899647
## [197] 16.907968 11.045111 16.173426 15.728736 16.320810 15.491665 16.792260
## [204] 16.252462 14.554001 13.755717 17.097396 11.210150 17.168315 15.158789
## [211] 13.786911 15.087905 14.395159 17.977321 15.164119 13.747828 12.065592
## [218] 17.625165 15.624490 17.089209 12.621621 13.606905 13.958527 14.585458
## [225] 13.647353 13.611843 14.431718 10.827125 14.614931 11.645749 20.182387
## [232] 16.201666 14.770738 16.613804 15.760049 17.050555 15.428902 13.410351
## [239] 13.535657 16.932934 13.725264 17.153194 17.191083 15.372936 15.905794
## [246] 11.677552 15.302182 17.955613 14.510289 13.026420 13.322574 14.228007
## [253] 14.680360 16.554579 16.716295 14.904950 17.393307 13.358643 12.209492
## [260] 13.688680 13.949290 17.456991 15.051724 13.666621 11.171995 15.898695
## [267] 16.084577 11.336023 17.566261 14.873494 12.558624 19.836118 13.598143
## [274] 11.690156 17.146837 17.908249 15.607811 13.603953 16.274669 14.796846
## [281] 14.071528 13.459806 15.448809 15.229750 15.865933 14.585737 10.604317
## [288] 14.780073 12.286362 14.334625 15.005137 14.469816 16.677490 14.923886
## [295] 20.812222 15.273856 15.272373 13.655172 13.304118 12.864425

response_2 <- rnorm(n=n[i], mean=30, sd=7)
print(response_2)

##   [1] 30.820920 40.949784 23.652864 34.197059 31.746392 39.227042 33.661915
##   [8] 47.290354 25.970212 27.436752 22.883091 36.448913 42.051998 36.229067
##  [15] 30.040644 25.853383 25.179574 31.878009 39.752674 12.389755 16.566226
##  [22] 18.004636 36.026126 24.795717 33.009281 31.033237 39.613304 21.103519
##  [29] 38.857069 26.114208 33.565569 39.048825 30.440948 18.985177 34.164913
##  [36] 38.636129 31.460808 30.564688 24.895255 36.709220 27.144751 30.893584
##  [43] 25.238045 26.968664 25.415005 28.247444 23.758652 22.904014 32.453240
##  [50] 29.165082 19.654272 21.766146 32.625326 35.298914 30.775541 30.963227
##  [57] 30.064504 30.673784 34.948335 21.484152 31.856784 41.803988 30.300005
##  [64] 41.330874 34.362716 26.051303 40.229275 31.565431 20.992666 24.321990
##  [71] 28.771713 33.985366 31.772843 27.201260 28.112552 28.706589 25.704317
##  [78] 33.033522 35.370073 31.353119 31.397026 37.629023 25.070888 23.078650
##  [85] 23.658146 24.009236 22.411221 45.110296 22.871481 39.816006 36.415149
##  [92] 26.956145 39.037146 29.480280 31.185757 35.596261 42.428578 29.345232
##  [99] 31.894954 26.454020 32.704885 30.714885 25.757651 29.857680  7.089324
## [106] 43.360671 26.143413 27.363938 25.331332 27.898239 19.275629 36.442477
## [113] 37.658841 32.683734 24.386978 37.608152 36.683652 41.422998 27.737338
## [120] 20.772613 36.986803 29.802783 17.233484 24.274584 42.305584 48.362133
## [127] 31.976935 34.468180 26.051261 39.086101 37.969500 23.569115 35.667563
## [134] 23.986131 36.669210 26.115450 19.396032 32.633887 33.191791 40.004485
## [141] 36.171165 28.870067 22.421685 20.169256 23.224656 33.510973 30.360109
## [148] 32.352670 28.582208 38.234964 20.405681 21.857409 35.789520 32.165857
## [155] 19.469996 39.598445 28.240732 31.533567 39.391508 28.761097 38.833973
## [162] 25.989128 32.699333 31.147904 25.447049 37.207082 23.885463 27.334193
## [169] 22.020393 32.032914 13.875401 34.121888 31.677704 39.768998 17.062398
## [176] 32.080058 19.859697 35.665338 32.212683 37.329143 36.103549 19.964710
## [183] 28.351916 41.111683 21.873869 27.299911 25.248364 24.107353 28.290011
## [190] 34.942515 29.107812 37.100789 17.471183 42.358443 32.217445 36.137340
## [197] 28.595259 28.753811 30.875654 27.416867 31.285908 36.236941 33.388109
## [204] 33.273358 27.490291 27.411790 28.434682 30.995734 27.097840 22.699612
## [211] 28.789511 27.417802 18.633444 43.932303 23.604233 27.544144 35.756936
## [218] 24.198091 32.040453 36.079853 33.053641 33.993698 40.562515 21.405445
## [225] 25.807576 21.179692 41.097143 25.002534 22.312019 20.614935 31.793494
## [232] 27.198065 34.233987 25.997388 38.664652 32.895531 22.702631 32.035850
## [239] 27.399792 25.927703 25.254016 19.501531 29.150578 41.786011 33.376293
## [246] 16.609296 34.151238 50.809338 28.413099 35.712477 38.997336 28.233273
## [253] 45.554199 40.871329 23.958668 32.026124 24.230296 28.553483 37.153185
## [260] 34.197921 30.726325 31.355753 26.219251 24.482994 36.947545 36.292529
## [267] 34.750015 24.168663 32.077175 35.797269 35.011045 33.843254 42.136630
## [274] 25.599147 31.826335 16.571375 30.512940 30.050261 14.711125 33.964377
## [281] 20.498825 39.986283 24.424753 25.032979 29.997364 24.854161 27.365933
## [288] 35.817324 26.778861 22.722832 25.175260 15.218219 23.030336 37.064135
## [295] 30.329333 33.017079 25.602207 33.906420 44.356362 23.734933

response <- c(response_1, response_2)

my_df_1 <- data.frame (X = "control", Y= response_1)
print(my_df_1)

##           X         Y
## 1   control 13.524850
## 2   control 16.162169
## 3   control 16.657575
## 4   control 16.137966
## 5   control 14.581420
## 6   control 13.858991
## 7   control 19.045828
## 8   control 15.545089
## 9   control 16.123825
## 10  control 14.299803
## 11  control 17.002045
## 12  control 15.759880
## 13  control 13.072970
## 14  control 15.938578
## 15  control 17.360188
## 16  control 14.209815
## 17  control 16.093269
## 18  control 12.860212
## 19  control  9.350368
## 20  control 12.861384
## 21  control 14.528101
## 22  control 10.982822
## 23  control 15.481775
## 24  control 13.808889
## 25  control 13.448322
## 26  control 14.072885
## 27  control 12.585229
## 28  control 12.172660
## 29  control 14.556322
## 30  control 17.678359
## 31  control 14.655668
## 32  control 15.725132
## 33  control 14.433328
## 34  control 15.558840
## 35  control 11.653116
## 36  control 17.674471
## 37  control 16.571423
## 38  control 13.002206
## 39  control 16.538782
## 40  control 15.968290
## 41  control 17.153381
## 42  control 14.505149
## 43  control 12.856031
## 44  control 14.059467
## 45  control 15.986151
## 46  control 18.383773
## 47  control 13.814169
## 48  control 14.831214
## 49  control 16.102674
## 50  control 19.286194
## 51  control 15.697546
## 52  control 13.068484
## 53  control 18.594191
## 54  control 16.735174
## 55  control 17.657626
## 56  control 15.113586
## 57  control 15.803128
## 58  control 14.408149
## 59  control 13.113259
## 60  control 13.961630
## 61  control 13.782922
## 62  control 13.897541
## 63  control 17.905224
## 64  control 19.509321
## 65  control 14.738527
## 66  control 15.362901
## 67  control 16.795910
## 68  control 16.732088
## 69  control 13.801756
## 70  control 13.211352
## 71  control 15.071874
## 72  control 19.484375
## 73  control 18.075572
## 74  control 15.875530
## 75  control 14.241704
## 76  control 13.654567
## 77  control 16.581585
## 78  control 17.743569
## 79  control 14.367956
## 80  control 12.141891
## 81  control 12.153958
## 82  control 18.626676
## 83  control 16.495305
## 84  control 16.645334
## 85  control 11.851035
## 86  control 16.081154
## 87  control 18.318775
## 88  control 14.754154
## 89  control 16.868047
## 90  control 16.724617
## 91  control 14.758559
## 92  control  9.475854
## 93  control 17.441484
## 94  control 13.897368
## 95  control 14.910525
## 96  control 15.814793
## 97  control 14.640143
## 98  control 15.078015
## 99  control 15.213515
## 100 control 15.706322
## 101 control 15.247965
## 102 control 13.146854
## 103 control 11.364270
## 104 control 16.077684
## 105 control 17.381601
## 106 control 15.414467
## 107 control 11.776056
## 108 control 14.750541
## 109 control 15.029076
## 110 control 16.208454
## 111 control 15.346990
## 112 control 15.673430
## 113 control 12.859934
## 114 control 18.057441
## 115 control 15.170795
## 116 control 12.473666
## 117 control 12.641136
## 118 control 15.331539
## 119 control 13.158327
## 120 control 15.958656
## 121 control 12.417232
## 122 control 16.215906
## 123 control 12.870563
## 124 control 12.593260
## 125 control 16.027780
## 126 control 13.462400
## 127 control 11.568257
## 128 control 17.962238
## 129 control 15.361641
## 130 control 11.963316
## 131 control 13.921920
## 132 control 14.612572
## 133 control 11.135482
## 134 control 14.291027
## 135 control 15.815209
## 136 control 16.685966
## 137 control 14.676643
## 138 control 17.567754
## 139 control 13.381781
## 140 control 17.090650
## 141 control 15.350637
## 142 control 16.125473
## 143 control 16.462265
## 144 control 14.320864
## 145 control 15.741398
## 146 control 14.697217
## 147 control 15.982210
## 148 control 14.956769
## 149 control 16.058912
## 150 control 14.840666
## 151 control 12.397339
## 152 control 15.608417
## 153 control 17.699649
## 154 control 10.813945
## 155 control 14.282665
## 156 control 13.553862
## 157 control 12.759383
## 158 control 16.478448
## 159 control 18.840037
## 160 control 14.934314
## 161 control 19.711098
## 162 control 16.524151
## 163 control 11.108402
## 164 control 11.926968
## 165 control 17.637653
## 166 control 14.013088
## 167 control 13.009632
## 168 control 17.991936
## 169 control 10.399573
## 170 control 12.858779
## 171 control 17.070789
## 172 control 19.007162
## 173 control 15.943364
## 174 control 14.028840
## 175 control 14.519849
## 176 control 12.383627
## 177 control 15.536302
## 178 control 17.772054
## 179 control 11.272484
## 180 control 16.663617
## 181 control 14.090546
## 182 control 11.269606
## 183 control 15.680611
## 184 control 10.637629
## 185 control 17.419836
## 186 control 11.937020
## 187 control 12.773752
## 188 control 14.118267
## 189 control 15.851570
## 190 control 12.293068
## 191 control 18.317905
## 192 control 13.546393
## 193 control 13.265006
## 194 control 14.940806
## 195 control 13.824269
## 196 control 14.899647
## 197 control 16.907968
## 198 control 11.045111
## 199 control 16.173426
## 200 control 15.728736
## 201 control 16.320810
## 202 control 15.491665
## 203 control 16.792260
## 204 control 16.252462
## 205 control 14.554001
## 206 control 13.755717
## 207 control 17.097396
## 208 control 11.210150
## 209 control 17.168315
## 210 control 15.158789
## 211 control 13.786911
## 212 control 15.087905
## 213 control 14.395159
## 214 control 17.977321
## 215 control 15.164119
## 216 control 13.747828
## 217 control 12.065592
## 218 control 17.625165
## 219 control 15.624490
## 220 control 17.089209
## 221 control 12.621621
## 222 control 13.606905
## 223 control 13.958527
## 224 control 14.585458
## 225 control 13.647353
## 226 control 13.611843
## 227 control 14.431718
## 228 control 10.827125
## 229 control 14.614931
## 230 control 11.645749
## 231 control 20.182387
## 232 control 16.201666
## 233 control 14.770738
## 234 control 16.613804
## 235 control 15.760049
## 236 control 17.050555
## 237 control 15.428902
## 238 control 13.410351
## 239 control 13.535657
## 240 control 16.932934
## 241 control 13.725264
## 242 control 17.153194
## 243 control 17.191083
## 244 control 15.372936
## 245 control 15.905794
## 246 control 11.677552
## 247 control 15.302182
## 248 control 17.955613
## 249 control 14.510289
## 250 control 13.026420
## 251 control 13.322574
## 252 control 14.228007
## 253 control 14.680360
## 254 control 16.554579
## 255 control 16.716295
## 256 control 14.904950
## 257 control 17.393307
## 258 control 13.358643
## 259 control 12.209492
## 260 control 13.688680
## 261 control 13.949290
## 262 control 17.456991
## 263 control 15.051724
## 264 control 13.666621
## 265 control 11.171995
## 266 control 15.898695
## 267 control 16.084577
## 268 control 11.336023
## 269 control 17.566261
## 270 control 14.873494
## 271 control 12.558624
## 272 control 19.836118
## 273 control 13.598143
## 274 control 11.690156
## 275 control 17.146837
## 276 control 17.908249
## 277 control 15.607811
## 278 control 13.603953
## 279 control 16.274669
## 280 control 14.796846
## 281 control 14.071528
## 282 control 13.459806
## 283 control 15.448809
## 284 control 15.229750
## 285 control 15.865933
## 286 control 14.585737
## 287 control 10.604317
## 288 control 14.780073
## 289 control 12.286362
## 290 control 14.334625
## 291 control 15.005137
## 292 control 14.469816
## 293 control 16.677490
## 294 control 14.923886
## 295 control 20.812222
## 296 control 15.273856
## 297 control 15.272373
## 298 control 13.655172
## 299 control 13.304118
## 300 control 12.864425

my_df_2 <- data.frame(X = "treatment", Y = response_2)
print(my_df_2)

##             X         Y
## 1   treatment 30.820920
## 2   treatment 40.949784
## 3   treatment 23.652864
## 4   treatment 34.197059
## 5   treatment 31.746392
## 6   treatment 39.227042
## 7   treatment 33.661915
## 8   treatment 47.290354
## 9   treatment 25.970212
## 10  treatment 27.436752
## 11  treatment 22.883091
## 12  treatment 36.448913
## 13  treatment 42.051998
## 14  treatment 36.229067
## 15  treatment 30.040644
## 16  treatment 25.853383
## 17  treatment 25.179574
## 18  treatment 31.878009
## 19  treatment 39.752674
## 20  treatment 12.389755
## 21  treatment 16.566226
## 22  treatment 18.004636
## 23  treatment 36.026126
## 24  treatment 24.795717
## 25  treatment 33.009281
## 26  treatment 31.033237
## 27  treatment 39.613304
## 28  treatment 21.103519
## 29  treatment 38.857069
## 30  treatment 26.114208
## 31  treatment 33.565569
## 32  treatment 39.048825
## 33  treatment 30.440948
## 34  treatment 18.985177
## 35  treatment 34.164913
## 36  treatment 38.636129
## 37  treatment 31.460808
## 38  treatment 30.564688
## 39  treatment 24.895255
## 40  treatment 36.709220
## 41  treatment 27.144751
## 42  treatment 30.893584
## 43  treatment 25.238045
## 44  treatment 26.968664
## 45  treatment 25.415005
## 46  treatment 28.247444
## 47  treatment 23.758652
## 48  treatment 22.904014
## 49  treatment 32.453240
## 50  treatment 29.165082
## 51  treatment 19.654272
## 52  treatment 21.766146
## 53  treatment 32.625326
## 54  treatment 35.298914
## 55  treatment 30.775541
## 56  treatment 30.963227
## 57  treatment 30.064504
## 58  treatment 30.673784
## 59  treatment 34.948335
## 60  treatment 21.484152
## 61  treatment 31.856784
## 62  treatment 41.803988
## 63  treatment 30.300005
## 64  treatment 41.330874
## 65  treatment 34.362716
## 66  treatment 26.051303
## 67  treatment 40.229275
## 68  treatment 31.565431
## 69  treatment 20.992666
## 70  treatment 24.321990
## 71  treatment 28.771713
## 72  treatment 33.985366
## 73  treatment 31.772843
## 74  treatment 27.201260
## 75  treatment 28.112552
## 76  treatment 28.706589
## 77  treatment 25.704317
## 78  treatment 33.033522
## 79  treatment 35.370073
## 80  treatment 31.353119
## 81  treatment 31.397026
## 82  treatment 37.629023
## 83  treatment 25.070888
## 84  treatment 23.078650
## 85  treatment 23.658146
## 86  treatment 24.009236
## 87  treatment 22.411221
## 88  treatment 45.110296
## 89  treatment 22.871481
## 90  treatment 39.816006
## 91  treatment 36.415149
## 92  treatment 26.956145
## 93  treatment 39.037146
## 94  treatment 29.480280
## 95  treatment 31.185757
## 96  treatment 35.596261
## 97  treatment 42.428578
## 98  treatment 29.345232
## 99  treatment 31.894954
## 100 treatment 26.454020
## 101 treatment 32.704885
## 102 treatment 30.714885
## 103 treatment 25.757651
## 104 treatment 29.857680
## 105 treatment  7.089324
## 106 treatment 43.360671
## 107 treatment 26.143413
## 108 treatment 27.363938
## 109 treatment 25.331332
## 110 treatment 27.898239
## 111 treatment 19.275629
## 112 treatment 36.442477
## 113 treatment 37.658841
## 114 treatment 32.683734
## 115 treatment 24.386978
## 116 treatment 37.608152
## 117 treatment 36.683652
## 118 treatment 41.422998
## 119 treatment 27.737338
## 120 treatment 20.772613
## 121 treatment 36.986803
## 122 treatment 29.802783
## 123 treatment 17.233484
## 124 treatment 24.274584
## 125 treatment 42.305584
## 126 treatment 48.362133
## 127 treatment 31.976935
## 128 treatment 34.468180
## 129 treatment 26.051261
## 130 treatment 39.086101
## 131 treatment 37.969500
## 132 treatment 23.569115
## 133 treatment 35.667563
## 134 treatment 23.986131
## 135 treatment 36.669210
## 136 treatment 26.115450
## 137 treatment 19.396032
## 138 treatment 32.633887
## 139 treatment 33.191791
## 140 treatment 40.004485
## 141 treatment 36.171165
## 142 treatment 28.870067
## 143 treatment 22.421685
## 144 treatment 20.169256
## 145 treatment 23.224656
## 146 treatment 33.510973
## 147 treatment 30.360109
## 148 treatment 32.352670
## 149 treatment 28.582208
## 150 treatment 38.234964
## 151 treatment 20.405681
## 152 treatment 21.857409
## 153 treatment 35.789520
## 154 treatment 32.165857
## 155 treatment 19.469996
## 156 treatment 39.598445
## 157 treatment 28.240732
## 158 treatment 31.533567
## 159 treatment 39.391508
## 160 treatment 28.761097
## 161 treatment 38.833973
## 162 treatment 25.989128
## 163 treatment 32.699333
## 164 treatment 31.147904
## 165 treatment 25.447049
## 166 treatment 37.207082
## 167 treatment 23.885463
## 168 treatment 27.334193
## 169 treatment 22.020393
## 170 treatment 32.032914
## 171 treatment 13.875401
## 172 treatment 34.121888
## 173 treatment 31.677704
## 174 treatment 39.768998
## 175 treatment 17.062398
## 176 treatment 32.080058
## 177 treatment 19.859697
## 178 treatment 35.665338
## 179 treatment 32.212683
## 180 treatment 37.329143
## 181 treatment 36.103549
## 182 treatment 19.964710
## 183 treatment 28.351916
## 184 treatment 41.111683
## 185 treatment 21.873869
## 186 treatment 27.299911
## 187 treatment 25.248364
## 188 treatment 24.107353
## 189 treatment 28.290011
## 190 treatment 34.942515
## 191 treatment 29.107812
## 192 treatment 37.100789
## 193 treatment 17.471183
## 194 treatment 42.358443
## 195 treatment 32.217445
## 196 treatment 36.137340
## 197 treatment 28.595259
## 198 treatment 28.753811
## 199 treatment 30.875654
## 200 treatment 27.416867
## 201 treatment 31.285908
## 202 treatment 36.236941
## 203 treatment 33.388109
## 204 treatment 33.273358
## 205 treatment 27.490291
## 206 treatment 27.411790
## 207 treatment 28.434682
## 208 treatment 30.995734
## 209 treatment 27.097840
## 210 treatment 22.699612
## 211 treatment 28.789511
## 212 treatment 27.417802
## 213 treatment 18.633444
## 214 treatment 43.932303
## 215 treatment 23.604233
## 216 treatment 27.544144
## 217 treatment 35.756936
## 218 treatment 24.198091
## 219 treatment 32.040453
## 220 treatment 36.079853
## 221 treatment 33.053641
## 222 treatment 33.993698
## 223 treatment 40.562515
## 224 treatment 21.405445
## 225 treatment 25.807576
## 226 treatment 21.179692
## 227 treatment 41.097143
## 228 treatment 25.002534
## 229 treatment 22.312019
## 230 treatment 20.614935
## 231 treatment 31.793494
## 232 treatment 27.198065
## 233 treatment 34.233987
## 234 treatment 25.997388
## 235 treatment 38.664652
## 236 treatment 32.895531
## 237 treatment 22.702631
## 238 treatment 32.035850
## 239 treatment 27.399792
## 240 treatment 25.927703
## 241 treatment 25.254016
## 242 treatment 19.501531
## 243 treatment 29.150578
## 244 treatment 41.786011
## 245 treatment 33.376293
## 246 treatment 16.609296
## 247 treatment 34.151238
## 248 treatment 50.809338
## 249 treatment 28.413099
## 250 treatment 35.712477
## 251 treatment 38.997336
## 252 treatment 28.233273
## 253 treatment 45.554199
## 254 treatment 40.871329
## 255 treatment 23.958668
## 256 treatment 32.026124
## 257 treatment 24.230296
## 258 treatment 28.553483
## 259 treatment 37.153185
## 260 treatment 34.197921
## 261 treatment 30.726325
## 262 treatment 31.355753
## 263 treatment 26.219251
## 264 treatment 24.482994
## 265 treatment 36.947545
## 266 treatment 36.292529
## 267 treatment 34.750015
## 268 treatment 24.168663
## 269 treatment 32.077175
## 270 treatment 35.797269
## 271 treatment 35.011045
## 272 treatment 33.843254
## 273 treatment 42.136630
## 274 treatment 25.599147
## 275 treatment 31.826335
## 276 treatment 16.571375
## 277 treatment 30.512940
## 278 treatment 30.050261
## 279 treatment 14.711125
## 280 treatment 33.964377
## 281 treatment 20.498825
## 282 treatment 39.986283
## 283 treatment 24.424753
## 284 treatment 25.032979
## 285 treatment 29.997364
## 286 treatment 24.854161
## 287 treatment 27.365933
## 288 treatment 35.817324
## 289 treatment 26.778861
## 290 treatment 22.722832
## 291 treatment 25.175260
## 292 treatment 15.218219
## 293 treatment 23.030336
## 294 treatment 37.064135
## 295 treatment 30.329333
## 296 treatment 33.017079
## 297 treatment 25.602207
## 298 treatment 33.906420
## 299 treatment 44.356362
## 300 treatment 23.734933

my_df <- rbind(my_df_1, my_df_2)
print(my_df)

##             X         Y
## 1     control 13.524850
## 2     control 16.162169
## 3     control 16.657575
## 4     control 16.137966
## 5     control 14.581420
## 6     control 13.858991
## 7     control 19.045828
## 8     control 15.545089
## 9     control 16.123825
## 10    control 14.299803
## 11    control 17.002045
## 12    control 15.759880
## 13    control 13.072970
## 14    control 15.938578
## 15    control 17.360188
## 16    control 14.209815
## 17    control 16.093269
## 18    control 12.860212
## 19    control  9.350368
## 20    control 12.861384
## 21    control 14.528101
## 22    control 10.982822
## 23    control 15.481775
## 24    control 13.808889
## 25    control 13.448322
## 26    control 14.072885
## 27    control 12.585229
## 28    control 12.172660
## 29    control 14.556322
## 30    control 17.678359
## 31    control 14.655668
## 32    control 15.725132
## 33    control 14.433328
## 34    control 15.558840
## 35    control 11.653116
## 36    control 17.674471
## 37    control 16.571423
## 38    control 13.002206
## 39    control 16.538782
## 40    control 15.968290
## 41    control 17.153381
## 42    control 14.505149
## 43    control 12.856031
## 44    control 14.059467
## 45    control 15.986151
## 46    control 18.383773
## 47    control 13.814169
## 48    control 14.831214
## 49    control 16.102674
## 50    control 19.286194
## 51    control 15.697546
## 52    control 13.068484
## 53    control 18.594191
## 54    control 16.735174
## 55    control 17.657626
## 56    control 15.113586
## 57    control 15.803128
## 58    control 14.408149
## 59    control 13.113259
## 60    control 13.961630
## 61    control 13.782922
## 62    control 13.897541
## 63    control 17.905224
## 64    control 19.509321
## 65    control 14.738527
## 66    control 15.362901
## 67    control 16.795910
## 68    control 16.732088
## 69    control 13.801756
## 70    control 13.211352
## 71    control 15.071874
## 72    control 19.484375
## 73    control 18.075572
## 74    control 15.875530
## 75    control 14.241704
## 76    control 13.654567
## 77    control 16.581585
## 78    control 17.743569
## 79    control 14.367956
## 80    control 12.141891
## 81    control 12.153958
## 82    control 18.626676
## 83    control 16.495305
## 84    control 16.645334
## 85    control 11.851035
## 86    control 16.081154
## 87    control 18.318775
## 88    control 14.754154
## 89    control 16.868047
## 90    control 16.724617
## 91    control 14.758559
## 92    control  9.475854
## 93    control 17.441484
## 94    control 13.897368
## 95    control 14.910525
## 96    control 15.814793
## 97    control 14.640143
## 98    control 15.078015
## 99    control 15.213515
## 100   control 15.706322
## 101   control 15.247965
## 102   control 13.146854
## 103   control 11.364270
## 104   control 16.077684
## 105   control 17.381601
## 106   control 15.414467
## 107   control 11.776056
## 108   control 14.750541
## 109   control 15.029076
## 110   control 16.208454
## 111   control 15.346990
## 112   control 15.673430
## 113   control 12.859934
## 114   control 18.057441
## 115   control 15.170795
## 116   control 12.473666
## 117   control 12.641136
## 118   control 15.331539
## 119   control 13.158327
## 120   control 15.958656
## 121   control 12.417232
## 122   control 16.215906
## 123   control 12.870563
## 124   control 12.593260
## 125   control 16.027780
## 126   control 13.462400
## 127   control 11.568257
## 128   control 17.962238
## 129   control 15.361641
## 130   control 11.963316
## 131   control 13.921920
## 132   control 14.612572
## 133   control 11.135482
## 134   control 14.291027
## 135   control 15.815209
## 136   control 16.685966
## 137   control 14.676643
## 138   control 17.567754
## 139   control 13.381781
## 140   control 17.090650
## 141   control 15.350637
## 142   control 16.125473
## 143   control 16.462265
## 144   control 14.320864
## 145   control 15.741398
## 146   control 14.697217
## 147   control 15.982210
## 148   control 14.956769
## 149   control 16.058912
## 150   control 14.840666
## 151   control 12.397339
## 152   control 15.608417
## 153   control 17.699649
## 154   control 10.813945
## 155   control 14.282665
## 156   control 13.553862
## 157   control 12.759383
## 158   control 16.478448
## 159   control 18.840037
## 160   control 14.934314
## 161   control 19.711098
## 162   control 16.524151
## 163   control 11.108402
## 164   control 11.926968
## 165   control 17.637653
## 166   control 14.013088
## 167   control 13.009632
## 168   control 17.991936
## 169   control 10.399573
## 170   control 12.858779
## 171   control 17.070789
## 172   control 19.007162
## 173   control 15.943364
## 174   control 14.028840
## 175   control 14.519849
## 176   control 12.383627
## 177   control 15.536302
## 178   control 17.772054
## 179   control 11.272484
## 180   control 16.663617
## 181   control 14.090546
## 182   control 11.269606
## 183   control 15.680611
## 184   control 10.637629
## 185   control 17.419836
## 186   control 11.937020
## 187   control 12.773752
## 188   control 14.118267
## 189   control 15.851570
## 190   control 12.293068
## 191   control 18.317905
## 192   control 13.546393
## 193   control 13.265006
## 194   control 14.940806
## 195   control 13.824269
## 196   control 14.899647
## 197   control 16.907968
## 198   control 11.045111
## 199   control 16.173426
## 200   control 15.728736
## 201   control 16.320810
## 202   control 15.491665
## 203   control 16.792260
## 204   control 16.252462
## 205   control 14.554001
## 206   control 13.755717
## 207   control 17.097396
## 208   control 11.210150
## 209   control 17.168315
## 210   control 15.158789
## 211   control 13.786911
## 212   control 15.087905
## 213   control 14.395159
## 214   control 17.977321
## 215   control 15.164119
## 216   control 13.747828
## 217   control 12.065592
## 218   control 17.625165
## 219   control 15.624490
## 220   control 17.089209
## 221   control 12.621621
## 222   control 13.606905
## 223   control 13.958527
## 224   control 14.585458
## 225   control 13.647353
## 226   control 13.611843
## 227   control 14.431718
## 228   control 10.827125
## 229   control 14.614931
## 230   control 11.645749
## 231   control 20.182387
## 232   control 16.201666
## 233   control 14.770738
## 234   control 16.613804
## 235   control 15.760049
## 236   control 17.050555
## 237   control 15.428902
## 238   control 13.410351
## 239   control 13.535657
## 240   control 16.932934
## 241   control 13.725264
## 242   control 17.153194
## 243   control 17.191083
## 244   control 15.372936
## 245   control 15.905794
## 246   control 11.677552
## 247   control 15.302182
## 248   control 17.955613
## 249   control 14.510289
## 250   control 13.026420
## 251   control 13.322574
## 252   control 14.228007
## 253   control 14.680360
## 254   control 16.554579
## 255   control 16.716295
## 256   control 14.904950
## 257   control 17.393307
## 258   control 13.358643
## 259   control 12.209492
## 260   control 13.688680
## 261   control 13.949290
## 262   control 17.456991
## 263   control 15.051724
## 264   control 13.666621
## 265   control 11.171995
## 266   control 15.898695
## 267   control 16.084577
## 268   control 11.336023
## 269   control 17.566261
## 270   control 14.873494
## 271   control 12.558624
## 272   control 19.836118
## 273   control 13.598143
## 274   control 11.690156
## 275   control 17.146837
## 276   control 17.908249
## 277   control 15.607811
## 278   control 13.603953
## 279   control 16.274669
## 280   control 14.796846
## 281   control 14.071528
## 282   control 13.459806
## 283   control 15.448809
## 284   control 15.229750
## 285   control 15.865933
## 286   control 14.585737
## 287   control 10.604317
## 288   control 14.780073
## 289   control 12.286362
## 290   control 14.334625
## 291   control 15.005137
## 292   control 14.469816
## 293   control 16.677490
## 294   control 14.923886
## 295   control 20.812222
## 296   control 15.273856
## 297   control 15.272373
## 298   control 13.655172
## 299   control 13.304118
## 300   control 12.864425
## 301 treatment 30.820920
## 302 treatment 40.949784
## 303 treatment 23.652864
## 304 treatment 34.197059
## 305 treatment 31.746392
## 306 treatment 39.227042
## 307 treatment 33.661915
## 308 treatment 47.290354
## 309 treatment 25.970212
## 310 treatment 27.436752
## 311 treatment 22.883091
## 312 treatment 36.448913
## 313 treatment 42.051998
## 314 treatment 36.229067
## 315 treatment 30.040644
## 316 treatment 25.853383
## 317 treatment 25.179574
## 318 treatment 31.878009
## 319 treatment 39.752674
## 320 treatment 12.389755
## 321 treatment 16.566226
## 322 treatment 18.004636
## 323 treatment 36.026126
## 324 treatment 24.795717
## 325 treatment 33.009281
## 326 treatment 31.033237
## 327 treatment 39.613304
## 328 treatment 21.103519
## 329 treatment 38.857069
## 330 treatment 26.114208
## 331 treatment 33.565569
## 332 treatment 39.048825
## 333 treatment 30.440948
## 334 treatment 18.985177
## 335 treatment 34.164913
## 336 treatment 38.636129
## 337 treatment 31.460808
## 338 treatment 30.564688
## 339 treatment 24.895255
## 340 treatment 36.709220
## 341 treatment 27.144751
## 342 treatment 30.893584
## 343 treatment 25.238045
## 344 treatment 26.968664
## 345 treatment 25.415005
## 346 treatment 28.247444
## 347 treatment 23.758652
## 348 treatment 22.904014
## 349 treatment 32.453240
## 350 treatment 29.165082
## 351 treatment 19.654272
## 352 treatment 21.766146
## 353 treatment 32.625326
## 354 treatment 35.298914
## 355 treatment 30.775541
## 356 treatment 30.963227
## 357 treatment 30.064504
## 358 treatment 30.673784
## 359 treatment 34.948335
## 360 treatment 21.484152
## 361 treatment 31.856784
## 362 treatment 41.803988
## 363 treatment 30.300005
## 364 treatment 41.330874
## 365 treatment 34.362716
## 366 treatment 26.051303
## 367 treatment 40.229275
## 368 treatment 31.565431
## 369 treatment 20.992666
## 370 treatment 24.321990
## 371 treatment 28.771713
## 372 treatment 33.985366
## 373 treatment 31.772843
## 374 treatment 27.201260
## 375 treatment 28.112552
## 376 treatment 28.706589
## 377 treatment 25.704317
## 378 treatment 33.033522
## 379 treatment 35.370073
## 380 treatment 31.353119
## 381 treatment 31.397026
## 382 treatment 37.629023
## 383 treatment 25.070888
## 384 treatment 23.078650
## 385 treatment 23.658146
## 386 treatment 24.009236
## 387 treatment 22.411221
## 388 treatment 45.110296
## 389 treatment 22.871481
## 390 treatment 39.816006
## 391 treatment 36.415149
## 392 treatment 26.956145
## 393 treatment 39.037146
## 394 treatment 29.480280
## 395 treatment 31.185757
## 396 treatment 35.596261
## 397 treatment 42.428578
## 398 treatment 29.345232
## 399 treatment 31.894954
## 400 treatment 26.454020
## 401 treatment 32.704885
## 402 treatment 30.714885
## 403 treatment 25.757651
## 404 treatment 29.857680
## 405 treatment  7.089324
## 406 treatment 43.360671
## 407 treatment 26.143413
## 408 treatment 27.363938
## 409 treatment 25.331332
## 410 treatment 27.898239
## 411 treatment 19.275629
## 412 treatment 36.442477
## 413 treatment 37.658841
## 414 treatment 32.683734
## 415 treatment 24.386978
## 416 treatment 37.608152
## 417 treatment 36.683652
## 418 treatment 41.422998
## 419 treatment 27.737338
## 420 treatment 20.772613
## 421 treatment 36.986803
## 422 treatment 29.802783
## 423 treatment 17.233484
## 424 treatment 24.274584
## 425 treatment 42.305584
## 426 treatment 48.362133
## 427 treatment 31.976935
## 428 treatment 34.468180
## 429 treatment 26.051261
## 430 treatment 39.086101
## 431 treatment 37.969500
## 432 treatment 23.569115
## 433 treatment 35.667563
## 434 treatment 23.986131
## 435 treatment 36.669210
## 436 treatment 26.115450
## 437 treatment 19.396032
## 438 treatment 32.633887
## 439 treatment 33.191791
## 440 treatment 40.004485
## 441 treatment 36.171165
## 442 treatment 28.870067
## 443 treatment 22.421685
## 444 treatment 20.169256
## 445 treatment 23.224656
## 446 treatment 33.510973
## 447 treatment 30.360109
## 448 treatment 32.352670
## 449 treatment 28.582208
## 450 treatment 38.234964
## 451 treatment 20.405681
## 452 treatment 21.857409
## 453 treatment 35.789520
## 454 treatment 32.165857
## 455 treatment 19.469996
## 456 treatment 39.598445
## 457 treatment 28.240732
## 458 treatment 31.533567
## 459 treatment 39.391508
## 460 treatment 28.761097
## 461 treatment 38.833973
## 462 treatment 25.989128
## 463 treatment 32.699333
## 464 treatment 31.147904
## 465 treatment 25.447049
## 466 treatment 37.207082
## 467 treatment 23.885463
## 468 treatment 27.334193
## 469 treatment 22.020393
## 470 treatment 32.032914
## 471 treatment 13.875401
## 472 treatment 34.121888
## 473 treatment 31.677704
## 474 treatment 39.768998
## 475 treatment 17.062398
## 476 treatment 32.080058
## 477 treatment 19.859697
## 478 treatment 35.665338
## 479 treatment 32.212683
## 480 treatment 37.329143
## 481 treatment 36.103549
## 482 treatment 19.964710
## 483 treatment 28.351916
## 484 treatment 41.111683
## 485 treatment 21.873869
## 486 treatment 27.299911
## 487 treatment 25.248364
## 488 treatment 24.107353
## 489 treatment 28.290011
## 490 treatment 34.942515
## 491 treatment 29.107812
## 492 treatment 37.100789
## 493 treatment 17.471183
## 494 treatment 42.358443
## 495 treatment 32.217445
## 496 treatment 36.137340
## 497 treatment 28.595259
## 498 treatment 28.753811
## 499 treatment 30.875654
## 500 treatment 27.416867
## 501 treatment 31.285908
## 502 treatment 36.236941
## 503 treatment 33.388109
## 504 treatment 33.273358
## 505 treatment 27.490291
## 506 treatment 27.411790
## 507 treatment 28.434682
## 508 treatment 30.995734
## 509 treatment 27.097840
## 510 treatment 22.699612
## 511 treatment 28.789511
## 512 treatment 27.417802
## 513 treatment 18.633444
## 514 treatment 43.932303
## 515 treatment 23.604233
## 516 treatment 27.544144
## 517 treatment 35.756936
## 518 treatment 24.198091
## 519 treatment 32.040453
## 520 treatment 36.079853
## 521 treatment 33.053641
## 522 treatment 33.993698
## 523 treatment 40.562515
## 524 treatment 21.405445
## 525 treatment 25.807576
## 526 treatment 21.179692
## 527 treatment 41.097143
## 528 treatment 25.002534
## 529 treatment 22.312019
## 530 treatment 20.614935
## 531 treatment 31.793494
## 532 treatment 27.198065
## 533 treatment 34.233987
## 534 treatment 25.997388
## 535 treatment 38.664652
## 536 treatment 32.895531
## 537 treatment 22.702631
## 538 treatment 32.035850
## 539 treatment 27.399792
## 540 treatment 25.927703
## 541 treatment 25.254016
## 542 treatment 19.501531
## 543 treatment 29.150578
## 544 treatment 41.786011
## 545 treatment 33.376293
## 546 treatment 16.609296
## 547 treatment 34.151238
## 548 treatment 50.809338
## 549 treatment 28.413099
## 550 treatment 35.712477
## 551 treatment 38.997336
## 552 treatment 28.233273
## 553 treatment 45.554199
## 554 treatment 40.871329
## 555 treatment 23.958668
## 556 treatment 32.026124
## 557 treatment 24.230296
## 558 treatment 28.553483
## 559 treatment 37.153185
## 560 treatment 34.197921
## 561 treatment 30.726325
## 562 treatment 31.355753
## 563 treatment 26.219251
## 564 treatment 24.482994
## 565 treatment 36.947545
## 566 treatment 36.292529
## 567 treatment 34.750015
## 568 treatment 24.168663
## 569 treatment 32.077175
## 570 treatment 35.797269
## 571 treatment 35.011045
## 572 treatment 33.843254
## 573 treatment 42.136630
## 574 treatment 25.599147
## 575 treatment 31.826335
## 576 treatment 16.571375
## 577 treatment 30.512940
## 578 treatment 30.050261
## 579 treatment 14.711125
## 580 treatment 33.964377
## 581 treatment 20.498825
## 582 treatment 39.986283
## 583 treatment 24.424753
## 584 treatment 25.032979
## 585 treatment 29.997364
## 586 treatment 24.854161
## 587 treatment 27.365933
## 588 treatment 35.817324
## 589 treatment 26.778861
## 590 treatment 22.722832
## 591 treatment 25.175260
## 592 treatment 15.218219
## 593 treatment 23.030336
## 594 treatment 37.064135
## 595 treatment 30.329333
## 596 treatment 33.017079
## 597 treatment 25.602207
## 598 treatment 33.906420
## 599 treatment 44.356362
## 600 treatment 23.734933

anova_data <- aov(Y ~ X, data = my_df)
summary_sample <- summary(anova_data)
print(summary_sample[[1]]$`Pr(>F)`)

## [1] 3.169333e-153            NA

library(ggplot2)
plot <- ggplot(my_df, aes(X, Y)) + geom_boxplot() + labs(x="Conditions",y="Responses")
print(plot)

Part 5

For Loop Generation- ADJUSTING MEAN

n <- sample(1:30)
for (i in 1:length(n)) {
  print(n[i])
}

## [1] 24
## [1] 13
## [1] 3
## [1] 17
## [1] 15
## [1] 26
## [1] 18
## [1] 2
## [1] 28
## [1] 20
## [1] 1
## [1] 29
## [1] 4
## [1] 30
## [1] 27
## [1] 14
## [1] 22
## [1] 5
## [1] 25
## [1] 6
## [1] 21
## [1] 11
## [1] 8
## [1] 12
## [1] 10
## [1] 19
## [1] 7
## [1] 16
## [1] 9
## [1] 23

response_1 <- rnorm(n=100, mean=n[i], sd=2)
print(response_1)

##   [1] 26.04050 20.35824 19.18019 20.42086 23.87200 27.25645 25.49615 28.90495
##   [9] 20.50034 23.24410 18.21611 23.03336 20.82951 22.36529 24.70948 18.99326
##  [17] 19.09105 24.14437 23.35244 20.05106 25.42369 20.77446 25.81284 26.32898
##  [25] 24.07293 22.25424 23.72169 26.92657 23.39062 21.14263 24.29616 21.55891
##  [33] 20.53001 21.23454 24.89717 17.96438 19.32548 23.81775 22.79821 22.52027
##  [41] 21.63986 23.76233 23.37679 22.99602 21.81976 23.99111 23.55036 20.46287
##  [49] 24.25894 26.00385 23.24186 24.71043 24.04533 25.38721 24.76128 22.32967
##  [57] 24.34771 25.40519 24.61430 22.31629 22.39975 22.10720 20.33718 22.97275
##  [65] 27.24901 25.71517 26.28858 21.69929 23.07604 23.07769 22.40196 20.53636
##  [73] 24.22320 21.58446 23.63752 23.06033 21.73805 22.34094 23.17614 24.30673
##  [81] 25.73159 21.44343 20.87715 23.81447 21.58263 21.25668 22.49560 22.88041
##  [89] 22.24215 19.85392 24.66313 18.67925 21.03124 27.16869 24.36504 21.31451
##  [97] 19.54139 19.36385 23.79630 22.92147

response_2 <- rnorm(n=100, mean=n[i], sd=7)
print(response_2)

##   [1] 30.944094 22.924934 17.951526 25.901292 23.257426 21.891159 16.793278
##   [8] 20.634830 29.689544 25.863514 20.432901 17.154858 26.116799 17.583507
##  [15] 26.773437 26.443264 12.465662 31.187157 27.012928 14.748377 20.906701
##  [22] 24.314022 22.110812 16.438075 25.744191 24.118487 30.694249 17.454126
##  [29] 25.591758 21.849298 27.140238 25.012847 20.969649 32.625292 31.406307
##  [36] 28.331172 25.731116 11.159584 16.778085 24.301618  6.060412 12.846596
##  [43] 10.457799 28.193711 26.300387 23.822415 28.285491 20.148066 23.911219
##  [50] 27.641883 10.337634 26.379667 16.635645 23.509003 19.100701 10.127575
##  [57] 17.035623 24.184382 24.784883 31.539616 22.132941 34.165084 16.450128
##  [64] 23.023389 13.216058  8.321844 23.432770 27.287029 30.475688 16.041016
##  [71] 27.079182 28.631010 34.797639 20.189810 14.832205 25.414427 25.418393
##  [78] 31.023198 25.777133 14.974672 27.830848 29.265200 13.697891 19.467684
##  [85] 35.592733 26.006307 22.612477 27.316395 28.265435 38.198896 10.202478
##  [92] 30.744122 23.733695 40.248665 21.086039 41.323108 22.894965 24.072240
##  [99] 28.434074 26.727434

response <- c(response_1, response_2)

my_df_1 <- data.frame (X = "control", Y= response_1)
print(my_df_1)

##           X        Y
## 1   control 26.04050
## 2   control 20.35824
## 3   control 19.18019
## 4   control 20.42086
## 5   control 23.87200
## 6   control 27.25645
## 7   control 25.49615
## 8   control 28.90495
## 9   control 20.50034
## 10  control 23.24410
## 11  control 18.21611
## 12  control 23.03336
## 13  control 20.82951
## 14  control 22.36529
## 15  control 24.70948
## 16  control 18.99326
## 17  control 19.09105
## 18  control 24.14437
## 19  control 23.35244
## 20  control 20.05106
## 21  control 25.42369
## 22  control 20.77446
## 23  control 25.81284
## 24  control 26.32898
## 25  control 24.07293
## 26  control 22.25424
## 27  control 23.72169
## 28  control 26.92657
## 29  control 23.39062
## 30  control 21.14263
## 31  control 24.29616
## 32  control 21.55891
## 33  control 20.53001
## 34  control 21.23454
## 35  control 24.89717
## 36  control 17.96438
## 37  control 19.32548
## 38  control 23.81775
## 39  control 22.79821
## 40  control 22.52027
## 41  control 21.63986
## 42  control 23.76233
## 43  control 23.37679
## 44  control 22.99602
## 45  control 21.81976
## 46  control 23.99111
## 47  control 23.55036
## 48  control 20.46287
## 49  control 24.25894
## 50  control 26.00385
## 51  control 23.24186
## 52  control 24.71043
## 53  control 24.04533
## 54  control 25.38721
## 55  control 24.76128
## 56  control 22.32967
## 57  control 24.34771
## 58  control 25.40519
## 59  control 24.61430
## 60  control 22.31629
## 61  control 22.39975
## 62  control 22.10720
## 63  control 20.33718
## 64  control 22.97275
## 65  control 27.24901
## 66  control 25.71517
## 67  control 26.28858
## 68  control 21.69929
## 69  control 23.07604
## 70  control 23.07769
## 71  control 22.40196
## 72  control 20.53636
## 73  control 24.22320
## 74  control 21.58446
## 75  control 23.63752
## 76  control 23.06033
## 77  control 21.73805
## 78  control 22.34094
## 79  control 23.17614
## 80  control 24.30673
## 81  control 25.73159
## 82  control 21.44343
## 83  control 20.87715
## 84  control 23.81447
## 85  control 21.58263
## 86  control 21.25668
## 87  control 22.49560
## 88  control 22.88041
## 89  control 22.24215
## 90  control 19.85392
## 91  control 24.66313
## 92  control 18.67925
## 93  control 21.03124
## 94  control 27.16869
## 95  control 24.36504
## 96  control 21.31451
## 97  control 19.54139
## 98  control 19.36385
## 99  control 23.79630
## 100 control 22.92147

my_df_2 <- data.frame(X = "treatment", Y = response_2)
print(my_df_2)

##             X         Y
## 1   treatment 30.944094
## 2   treatment 22.924934
## 3   treatment 17.951526
## 4   treatment 25.901292
## 5   treatment 23.257426
## 6   treatment 21.891159
## 7   treatment 16.793278
## 8   treatment 20.634830
## 9   treatment 29.689544
## 10  treatment 25.863514
## 11  treatment 20.432901
## 12  treatment 17.154858
## 13  treatment 26.116799
## 14  treatment 17.583507
## 15  treatment 26.773437
## 16  treatment 26.443264
## 17  treatment 12.465662
## 18  treatment 31.187157
## 19  treatment 27.012928
## 20  treatment 14.748377
## 21  treatment 20.906701
## 22  treatment 24.314022
## 23  treatment 22.110812
## 24  treatment 16.438075
## 25  treatment 25.744191
## 26  treatment 24.118487
## 27  treatment 30.694249
## 28  treatment 17.454126
## 29  treatment 25.591758
## 30  treatment 21.849298
## 31  treatment 27.140238
## 32  treatment 25.012847
## 33  treatment 20.969649
## 34  treatment 32.625292
## 35  treatment 31.406307
## 36  treatment 28.331172
## 37  treatment 25.731116
## 38  treatment 11.159584
## 39  treatment 16.778085
## 40  treatment 24.301618
## 41  treatment  6.060412
## 42  treatment 12.846596
## 43  treatment 10.457799
## 44  treatment 28.193711
## 45  treatment 26.300387
## 46  treatment 23.822415
## 47  treatment 28.285491
## 48  treatment 20.148066
## 49  treatment 23.911219
## 50  treatment 27.641883
## 51  treatment 10.337634
## 52  treatment 26.379667
## 53  treatment 16.635645
## 54  treatment 23.509003
## 55  treatment 19.100701
## 56  treatment 10.127575
## 57  treatment 17.035623
## 58  treatment 24.184382
## 59  treatment 24.784883
## 60  treatment 31.539616
## 61  treatment 22.132941
## 62  treatment 34.165084
## 63  treatment 16.450128
## 64  treatment 23.023389
## 65  treatment 13.216058
## 66  treatment  8.321844
## 67  treatment 23.432770
## 68  treatment 27.287029
## 69  treatment 30.475688
## 70  treatment 16.041016
## 71  treatment 27.079182
## 72  treatment 28.631010
## 73  treatment 34.797639
## 74  treatment 20.189810
## 75  treatment 14.832205
## 76  treatment 25.414427
## 77  treatment 25.418393
## 78  treatment 31.023198
## 79  treatment 25.777133
## 80  treatment 14.974672
## 81  treatment 27.830848
## 82  treatment 29.265200
## 83  treatment 13.697891
## 84  treatment 19.467684
## 85  treatment 35.592733
## 86  treatment 26.006307
## 87  treatment 22.612477
## 88  treatment 27.316395
## 89  treatment 28.265435
## 90  treatment 38.198896
## 91  treatment 10.202478
## 92  treatment 30.744122
## 93  treatment 23.733695
## 94  treatment 40.248665
## 95  treatment 21.086039
## 96  treatment 41.323108
## 97  treatment 22.894965
## 98  treatment 24.072240
## 99  treatment 28.434074
## 100 treatment 26.727434

my_df <- rbind(my_df_1, my_df_2)
print(my_df)

##             X         Y
## 1     control 26.040504
## 2     control 20.358236
## 3     control 19.180194
## 4     control 20.420859
## 5     control 23.871996
## 6     control 27.256450
## 7     control 25.496147
## 8     control 28.904953
## 9     control 20.500345
## 10    control 23.244102
## 11    control 18.216115
## 12    control 23.033358
## 13    control 20.829506
## 14    control 22.365293
## 15    control 24.709476
## 16    control 18.993265
## 17    control 19.091052
## 18    control 24.144367
## 19    control 23.352436
## 20    control 20.051062
## 21    control 25.423689
## 22    control 20.774457
## 23    control 25.812836
## 24    control 26.328976
## 25    control 24.072930
## 26    control 22.254243
## 27    control 23.721691
## 28    control 26.926567
## 29    control 23.390620
## 30    control 21.142626
## 31    control 24.296160
## 32    control 21.558910
## 33    control 20.530015
## 34    control 21.234545
## 35    control 24.897174
## 36    control 17.964379
## 37    control 19.325479
## 38    control 23.817755
## 39    control 22.798210
## 40    control 22.520270
## 41    control 21.639855
## 42    control 23.762330
## 43    control 23.376789
## 44    control 22.996020
## 45    control 21.819764
## 46    control 23.991105
## 47    control 23.550363
## 48    control 20.462870
## 49    control 24.258938
## 50    control 26.003848
## 51    control 23.241861
## 52    control 24.710428
## 53    control 24.045332
## 54    control 25.387207
## 55    control 24.761282
## 56    control 22.329665
## 57    control 24.347711
## 58    control 25.405193
## 59    control 24.614297
## 60    control 22.316286
## 61    control 22.399753
## 62    control 22.107204
## 63    control 20.337185
## 64    control 22.972751
## 65    control 27.249014
## 66    control 25.715172
## 67    control 26.288581
## 68    control 21.699288
## 69    control 23.076035
## 70    control 23.077689
## 71    control 22.401956
## 72    control 20.536364
## 73    control 24.223201
## 74    control 21.584462
## 75    control 23.637522
## 76    control 23.060326
## 77    control 21.738045
## 78    control 22.340945
## 79    control 23.176139
## 80    control 24.306734
## 81    control 25.731590
## 82    control 21.443433
## 83    control 20.877149
## 84    control 23.814465
## 85    control 21.582631
## 86    control 21.256677
## 87    control 22.495603
## 88    control 22.880414
## 89    control 22.242150
## 90    control 19.853922
## 91    control 24.663131
## 92    control 18.679247
## 93    control 21.031239
## 94    control 27.168688
## 95    control 24.365043
## 96    control 21.314513
## 97    control 19.541390
## 98    control 19.363848
## 99    control 23.796303
## 100   control 22.921473
## 101 treatment 30.944094
## 102 treatment 22.924934
## 103 treatment 17.951526
## 104 treatment 25.901292
## 105 treatment 23.257426
## 106 treatment 21.891159
## 107 treatment 16.793278
## 108 treatment 20.634830
## 109 treatment 29.689544
## 110 treatment 25.863514
## 111 treatment 20.432901
## 112 treatment 17.154858
## 113 treatment 26.116799
## 114 treatment 17.583507
## 115 treatment 26.773437
## 116 treatment 26.443264
## 117 treatment 12.465662
## 118 treatment 31.187157
## 119 treatment 27.012928
## 120 treatment 14.748377
## 121 treatment 20.906701
## 122 treatment 24.314022
## 123 treatment 22.110812
## 124 treatment 16.438075
## 125 treatment 25.744191
## 126 treatment 24.118487
## 127 treatment 30.694249
## 128 treatment 17.454126
## 129 treatment 25.591758
## 130 treatment 21.849298
## 131 treatment 27.140238
## 132 treatment 25.012847
## 133 treatment 20.969649
## 134 treatment 32.625292
## 135 treatment 31.406307
## 136 treatment 28.331172
## 137 treatment 25.731116
## 138 treatment 11.159584
## 139 treatment 16.778085
## 140 treatment 24.301618
## 141 treatment  6.060412
## 142 treatment 12.846596
## 143 treatment 10.457799
## 144 treatment 28.193711
## 145 treatment 26.300387
## 146 treatment 23.822415
## 147 treatment 28.285491
## 148 treatment 20.148066
## 149 treatment 23.911219
## 150 treatment 27.641883
## 151 treatment 10.337634
## 152 treatment 26.379667
## 153 treatment 16.635645
## 154 treatment 23.509003
## 155 treatment 19.100701
## 156 treatment 10.127575
## 157 treatment 17.035623
## 158 treatment 24.184382
## 159 treatment 24.784883
## 160 treatment 31.539616
## 161 treatment 22.132941
## 162 treatment 34.165084
## 163 treatment 16.450128
## 164 treatment 23.023389
## 165 treatment 13.216058
## 166 treatment  8.321844
## 167 treatment 23.432770
## 168 treatment 27.287029
## 169 treatment 30.475688
## 170 treatment 16.041016
## 171 treatment 27.079182
## 172 treatment 28.631010
## 173 treatment 34.797639
## 174 treatment 20.189810
## 175 treatment 14.832205
## 176 treatment 25.414427
## 177 treatment 25.418393
## 178 treatment 31.023198
## 179 treatment 25.777133
## 180 treatment 14.974672
## 181 treatment 27.830848
## 182 treatment 29.265200
## 183 treatment 13.697891
## 184 treatment 19.467684
## 185 treatment 35.592733
## 186 treatment 26.006307
## 187 treatment 22.612477
## 188 treatment 27.316395
## 189 treatment 28.265435
## 190 treatment 38.198896
## 191 treatment 10.202478
## 192 treatment 30.744122
## 193 treatment 23.733695
## 194 treatment 40.248665
## 195 treatment 21.086039
## 196 treatment 41.323108
## 197 treatment 22.894965
## 198 treatment 24.072240
## 199 treatment 28.434074
## 200 treatment 26.727434

anova_data <- aov(Y ~ X, data = my_df)
summary_mean <- summary(anova_data)
print(summary_mean[[1]]$`Pr(>F)`)

## [1] 0.4828797        NA

library(ggplot2)
plot <- ggplot(my_df, aes(X, Y)) + geom_boxplot() + labs(x="Conditions",y="Responses")
print(plot)

Part 6

For Loop Generation- ADJUSTING SD

n <- sample(1:20)
for (i in 1:length(n)) {
  print(n[i])
}

## [1] 7
## [1] 17
## [1] 10
## [1] 20
## [1] 11
## [1] 13
## [1] 2
## [1] 9
## [1] 4
## [1] 19
## [1] 1
## [1] 15
## [1] 16
## [1] 3
## [1] 12
## [1] 5
## [1] 14
## [1] 18
## [1] 8
## [1] 6

response_1 <- rnorm(n=100, mean=15, sd=n[i])
print(response_1)

##   [1] 17.676593 10.662276 14.908219 14.989702 15.539356 22.920482  8.452428
##   [8] 13.823333 17.869271 17.167750 17.493285 25.957156 18.237168 16.920656
##  [15] 26.260512  8.053655 20.089774 20.287404 16.287061 12.548225 18.404210
##  [22] 24.861803 16.145675 14.913415 10.986219 18.527094 22.754303  2.119349
##  [29] 20.650504 16.463844  8.309374 14.067918 18.976416 24.669917 19.805689
##  [36] 20.004288  8.342159 13.211073 27.859724 14.348384 13.533728 14.568267
##  [43] 20.087883 14.410646 12.958851 18.009119 23.823203 17.405299 18.308978
##  [50] 15.367859  5.244398 26.458036 19.025523 10.978125 13.090803 12.352106
##  [57] 19.734898 11.394264  9.565935 10.608874 15.617549 17.076025  8.617094
##  [64] 12.024605 16.061796 13.713561 22.993993 16.510807  9.585999 16.378742
##  [71] 16.629127 20.005746 19.164786 12.899626 23.193435 12.367855 17.450816
##  [78] 16.859506 12.712216 16.399401 13.117901 13.549320 20.114172  8.853243
##  [85] 10.438932  7.682258  4.746283  5.557751 18.081799 12.730521 12.920263
##  [92] 17.287760 11.135251 20.134838 17.059497 15.817510 18.915666 18.165938
##  [99]  9.219308 20.717517

response_2 <- rnorm(n=100, mean=30, sd=n[i])
print(response_2)

##   [1] 23.87950 29.63887 35.83025 26.69430 22.55854 24.92075 28.90276 43.00570
##   [9] 20.00068 36.62771 32.02478 29.64709 29.22741 24.44453 19.88974 31.07160
##  [17] 36.69393 34.89674 29.25308 36.68001 24.10011 28.04039 31.89184 26.99843
##  [25] 33.76505 32.42250 33.13567 30.60608 30.74482 31.27873 25.76428 33.36353
##  [33] 29.36696 22.86952 23.43021 25.68065 25.07785 24.56508 22.88572 36.72571
##  [41] 26.92072 34.43626 29.73319 36.64186 33.05586 20.04292 38.32365 36.13213
##  [49] 14.08289 20.05567 41.88438 26.33223 26.68149 26.14435 27.47687 35.72044
##  [57] 23.88652 28.87456 32.38710 34.78435 30.99241 32.36282 41.74655 39.44833
##  [65] 24.97460 35.41232 34.46546 31.05821 25.01566 27.05203 25.77636 34.71391
##  [73] 31.62926 28.00979 34.43779 19.53013 28.21313 20.24404 38.89469 29.72567
##  [81] 26.67099 35.04587 22.30902 40.15076 30.32942 18.88831 34.56833 38.70456
##  [89] 30.86703 28.74982 29.54270 31.32096 28.40390 35.65185 23.71123 36.42908
##  [97] 31.62649 29.50764 24.11962 24.23463

response <- c(response_1, response_2)

my_df_1 <- data.frame (X = "control", Y= response_1)
print(my_df_1)

##           X         Y
## 1   control 17.676593
## 2   control 10.662276
## 3   control 14.908219
## 4   control 14.989702
## 5   control 15.539356
## 6   control 22.920482
## 7   control  8.452428
## 8   control 13.823333
## 9   control 17.869271
## 10  control 17.167750
## 11  control 17.493285
## 12  control 25.957156
## 13  control 18.237168
## 14  control 16.920656
## 15  control 26.260512
## 16  control  8.053655
## 17  control 20.089774
## 18  control 20.287404
## 19  control 16.287061
## 20  control 12.548225
## 21  control 18.404210
## 22  control 24.861803
## 23  control 16.145675
## 24  control 14.913415
## 25  control 10.986219
## 26  control 18.527094
## 27  control 22.754303
## 28  control  2.119349
## 29  control 20.650504
## 30  control 16.463844
## 31  control  8.309374
## 32  control 14.067918
## 33  control 18.976416
## 34  control 24.669917
## 35  control 19.805689
## 36  control 20.004288
## 37  control  8.342159
## 38  control 13.211073
## 39  control 27.859724
## 40  control 14.348384
## 41  control 13.533728
## 42  control 14.568267
## 43  control 20.087883
## 44  control 14.410646
## 45  control 12.958851
## 46  control 18.009119
## 47  control 23.823203
## 48  control 17.405299
## 49  control 18.308978
## 50  control 15.367859
## 51  control  5.244398
## 52  control 26.458036
## 53  control 19.025523
## 54  control 10.978125
## 55  control 13.090803
## 56  control 12.352106
## 57  control 19.734898
## 58  control 11.394264
## 59  control  9.565935
## 60  control 10.608874
## 61  control 15.617549
## 62  control 17.076025
## 63  control  8.617094
## 64  control 12.024605
## 65  control 16.061796
## 66  control 13.713561
## 67  control 22.993993
## 68  control 16.510807
## 69  control  9.585999
## 70  control 16.378742
## 71  control 16.629127
## 72  control 20.005746
## 73  control 19.164786
## 74  control 12.899626
## 75  control 23.193435
## 76  control 12.367855
## 77  control 17.450816
## 78  control 16.859506
## 79  control 12.712216
## 80  control 16.399401
## 81  control 13.117901
## 82  control 13.549320
## 83  control 20.114172
## 84  control  8.853243
## 85  control 10.438932
## 86  control  7.682258
## 87  control  4.746283
## 88  control  5.557751
## 89  control 18.081799
## 90  control 12.730521
## 91  control 12.920263
## 92  control 17.287760
## 93  control 11.135251
## 94  control 20.134838
## 95  control 17.059497
## 96  control 15.817510
## 97  control 18.915666
## 98  control 18.165938
## 99  control  9.219308
## 100 control 20.717517

my_df_2 <- data.frame(X = "treatment", Y = response_2)
print(my_df_2)

##             X        Y
## 1   treatment 23.87950
## 2   treatment 29.63887
## 3   treatment 35.83025
## 4   treatment 26.69430
## 5   treatment 22.55854
## 6   treatment 24.92075
## 7   treatment 28.90276
## 8   treatment 43.00570
## 9   treatment 20.00068
## 10  treatment 36.62771
## 11  treatment 32.02478
## 12  treatment 29.64709
## 13  treatment 29.22741
## 14  treatment 24.44453
## 15  treatment 19.88974
## 16  treatment 31.07160
## 17  treatment 36.69393
## 18  treatment 34.89674
## 19  treatment 29.25308
## 20  treatment 36.68001
## 21  treatment 24.10011
## 22  treatment 28.04039
## 23  treatment 31.89184
## 24  treatment 26.99843
## 25  treatment 33.76505
## 26  treatment 32.42250
## 27  treatment 33.13567
## 28  treatment 30.60608
## 29  treatment 30.74482
## 30  treatment 31.27873
## 31  treatment 25.76428
## 32  treatment 33.36353
## 33  treatment 29.36696
## 34  treatment 22.86952
## 35  treatment 23.43021
## 36  treatment 25.68065
## 37  treatment 25.07785
## 38  treatment 24.56508
## 39  treatment 22.88572
## 40  treatment 36.72571
## 41  treatment 26.92072
## 42  treatment 34.43626
## 43  treatment 29.73319
## 44  treatment 36.64186
## 45  treatment 33.05586
## 46  treatment 20.04292
## 47  treatment 38.32365
## 48  treatment 36.13213
## 49  treatment 14.08289
## 50  treatment 20.05567
## 51  treatment 41.88438
## 52  treatment 26.33223
## 53  treatment 26.68149
## 54  treatment 26.14435
## 55  treatment 27.47687
## 56  treatment 35.72044
## 57  treatment 23.88652
## 58  treatment 28.87456
## 59  treatment 32.38710
## 60  treatment 34.78435
## 61  treatment 30.99241
## 62  treatment 32.36282
## 63  treatment 41.74655
## 64  treatment 39.44833
## 65  treatment 24.97460
## 66  treatment 35.41232
## 67  treatment 34.46546
## 68  treatment 31.05821
## 69  treatment 25.01566
## 70  treatment 27.05203
## 71  treatment 25.77636
## 72  treatment 34.71391
## 73  treatment 31.62926
## 74  treatment 28.00979
## 75  treatment 34.43779
## 76  treatment 19.53013
## 77  treatment 28.21313
## 78  treatment 20.24404
## 79  treatment 38.89469
## 80  treatment 29.72567
## 81  treatment 26.67099
## 82  treatment 35.04587
## 83  treatment 22.30902
## 84  treatment 40.15076
## 85  treatment 30.32942
## 86  treatment 18.88831
## 87  treatment 34.56833
## 88  treatment 38.70456
## 89  treatment 30.86703
## 90  treatment 28.74982
## 91  treatment 29.54270
## 92  treatment 31.32096
## 93  treatment 28.40390
## 94  treatment 35.65185
## 95  treatment 23.71123
## 96  treatment 36.42908
## 97  treatment 31.62649
## 98  treatment 29.50764
## 99  treatment 24.11962
## 100 treatment 24.23463

my_df <- rbind(my_df_1, my_df_2)
print(my_df)

##             X         Y
## 1     control 17.676593
## 2     control 10.662276
## 3     control 14.908219
## 4     control 14.989702
## 5     control 15.539356
## 6     control 22.920482
## 7     control  8.452428
## 8     control 13.823333
## 9     control 17.869271
## 10    control 17.167750
## 11    control 17.493285
## 12    control 25.957156
## 13    control 18.237168
## 14    control 16.920656
## 15    control 26.260512
## 16    control  8.053655
## 17    control 20.089774
## 18    control 20.287404
## 19    control 16.287061
## 20    control 12.548225
## 21    control 18.404210
## 22    control 24.861803
## 23    control 16.145675
## 24    control 14.913415
## 25    control 10.986219
## 26    control 18.527094
## 27    control 22.754303
## 28    control  2.119349
## 29    control 20.650504
## 30    control 16.463844
## 31    control  8.309374
## 32    control 14.067918
## 33    control 18.976416
## 34    control 24.669917
## 35    control 19.805689
## 36    control 20.004288
## 37    control  8.342159
## 38    control 13.211073
## 39    control 27.859724
## 40    control 14.348384
## 41    control 13.533728
## 42    control 14.568267
## 43    control 20.087883
## 44    control 14.410646
## 45    control 12.958851
## 46    control 18.009119
## 47    control 23.823203
## 48    control 17.405299
## 49    control 18.308978
## 50    control 15.367859
## 51    control  5.244398
## 52    control 26.458036
## 53    control 19.025523
## 54    control 10.978125
## 55    control 13.090803
## 56    control 12.352106
## 57    control 19.734898
## 58    control 11.394264
## 59    control  9.565935
## 60    control 10.608874
## 61    control 15.617549
## 62    control 17.076025
## 63    control  8.617094
## 64    control 12.024605
## 65    control 16.061796
## 66    control 13.713561
## 67    control 22.993993
## 68    control 16.510807
## 69    control  9.585999
## 70    control 16.378742
## 71    control 16.629127
## 72    control 20.005746
## 73    control 19.164786
## 74    control 12.899626
## 75    control 23.193435
## 76    control 12.367855
## 77    control 17.450816
## 78    control 16.859506
## 79    control 12.712216
## 80    control 16.399401
## 81    control 13.117901
## 82    control 13.549320
## 83    control 20.114172
## 84    control  8.853243
## 85    control 10.438932
## 86    control  7.682258
## 87    control  4.746283
## 88    control  5.557751
## 89    control 18.081799
## 90    control 12.730521
## 91    control 12.920263
## 92    control 17.287760
## 93    control 11.135251
## 94    control 20.134838
## 95    control 17.059497
## 96    control 15.817510
## 97    control 18.915666
## 98    control 18.165938
## 99    control  9.219308
## 100   control 20.717517
## 101 treatment 23.879504
## 102 treatment 29.638870
## 103 treatment 35.830251
## 104 treatment 26.694298
## 105 treatment 22.558538
## 106 treatment 24.920753
## 107 treatment 28.902764
## 108 treatment 43.005704
## 109 treatment 20.000676
## 110 treatment 36.627711
## 111 treatment 32.024778
## 112 treatment 29.647090
## 113 treatment 29.227415
## 114 treatment 24.444534
## 115 treatment 19.889739
## 116 treatment 31.071597
## 117 treatment 36.693928
## 118 treatment 34.896743
## 119 treatment 29.253082
## 120 treatment 36.680006
## 121 treatment 24.100107
## 122 treatment 28.040393
## 123 treatment 31.891841
## 124 treatment 26.998427
## 125 treatment 33.765048
## 126 treatment 32.422503
## 127 treatment 33.135666
## 128 treatment 30.606076
## 129 treatment 30.744823
## 130 treatment 31.278725
## 131 treatment 25.764284
## 132 treatment 33.363527
## 133 treatment 29.366957
## 134 treatment 22.869523
## 135 treatment 23.430213
## 136 treatment 25.680651
## 137 treatment 25.077851
## 138 treatment 24.565083
## 139 treatment 22.885717
## 140 treatment 36.725714
## 141 treatment 26.920717
## 142 treatment 34.436262
## 143 treatment 29.733192
## 144 treatment 36.641859
## 145 treatment 33.055862
## 146 treatment 20.042923
## 147 treatment 38.323655
## 148 treatment 36.132131
## 149 treatment 14.082888
## 150 treatment 20.055671
## 151 treatment 41.884379
## 152 treatment 26.332227
## 153 treatment 26.681487
## 154 treatment 26.144349
## 155 treatment 27.476874
## 156 treatment 35.720437
## 157 treatment 23.886524
## 158 treatment 28.874562
## 159 treatment 32.387096
## 160 treatment 34.784350
## 161 treatment 30.992415
## 162 treatment 32.362822
## 163 treatment 41.746552
## 164 treatment 39.448327
## 165 treatment 24.974605
## 166 treatment 35.412319
## 167 treatment 34.465458
## 168 treatment 31.058205
## 169 treatment 25.015665
## 170 treatment 27.052028
## 171 treatment 25.776364
## 172 treatment 34.713911
## 173 treatment 31.629260
## 174 treatment 28.009787
## 175 treatment 34.437789
## 176 treatment 19.530129
## 177 treatment 28.213128
## 178 treatment 20.244042
## 179 treatment 38.894686
## 180 treatment 29.725668
## 181 treatment 26.670986
## 182 treatment 35.045869
## 183 treatment 22.309018
## 184 treatment 40.150760
## 185 treatment 30.329425
## 186 treatment 18.888310
## 187 treatment 34.568334
## 188 treatment 38.704563
## 189 treatment 30.867032
## 190 treatment 28.749824
## 191 treatment 29.542700
## 192 treatment 31.320960
## 193 treatment 28.403899
## 194 treatment 35.651853
## 195 treatment 23.711229
## 196 treatment 36.429082
## 197 treatment 31.626490
## 198 treatment 29.507640
## 199 treatment 24.119622
## 200 treatment 24.234634

anova_data <- aov(Y ~ X, data = my_df)
summary_sd <- summary(anova_data)
print(summary_sd[[1]]$`Pr(>F)`)

## [1] 3.890713e-44           NA

library(ggplot2)
plot <- ggplot(my_df, aes(X, Y)) + geom_boxplot() + labs(x="Conditions",y="Responses")
print(plot)

Part 7

Comparing p-values

print(summary[[1]]$`Pr(>F)`)

## [1] 7.755695e-55           NA

print(summary_sample[[1]]$`Pr(>F)`)

## [1] 3.169333e-153            NA

print(summary_mean[[1]]$`Pr(>F)`)

## [1] 0.4828797        NA

print(summary_sd[[1]]$`Pr(>F)`)

## [1] 3.890713e-44           NA

Part 8

Discussion on p-values

1. When changing the sample size, the p-value became more significant.
2. When changing the mean, the p-value became insignificant.
3. When changing the standard deviation, the p-value became more significant.