This would be one way to do it
sample <- purrr::map_dfc(1:50, ~ list(sample = rnorm(100,100,25)))
sample
#> # A tibble: 100 x 50
#> sample sample1 sample2 sample3 sample4 sample5 sample6 sample7 sample8
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 88.2 129. 84.6 137. 107. 139. 75.4 120. 82.0
#> 2 108. 118. 95.3 126. 93.2 80.3 62.2 99.7 128.
#> 3 89.0 88.1 89.6 127. 106. 88.0 106. 149. 108.
#> 4 108. 90.2 115. 112. 93.8 102. 101. 93.8 120.
#> 5 105. 106. 78.9 91.7 95.3 98.4 70.9 122. 85.3
#> 6 95.9 85.0 112. 133. 73.8 128. 126. 83.9 97.7
#> 7 126. 163. 116. 120. 63.6 75.1 92.9 86.3 112.
#> 8 57.5 142. 119. 95.8 103. 121. 114. 117. 100.
#> 9 128. 91.1 94.1 115. 141. 88.6 103. 91.0 65.8
#> 10 54.6 123. 87.5 111. 149. 163. 119. 91.8 108.
#> # … with 90 more rows, and 41 more variables: sample9 <dbl>,
#> # sample10 <dbl>, sample11 <dbl>, sample12 <dbl>, sample13 <dbl>,
#> # sample14 <dbl>, sample15 <dbl>, sample16 <dbl>, sample17 <dbl>,
#> # sample18 <dbl>, sample19 <dbl>, sample20 <dbl>, sample21 <dbl>,
#> # sample22 <dbl>, sample23 <dbl>, sample24 <dbl>, sample25 <dbl>,
#> # sample26 <dbl>, sample27 <dbl>, sample28 <dbl>, sample29 <dbl>,
#> # sample30 <dbl>, sample31 <dbl>, sample32 <dbl>, sample33 <dbl>,
#> # sample34 <dbl>, sample35 <dbl>, sample36 <dbl>, sample37 <dbl>,
#> # sample38 <dbl>, sample39 <dbl>, sample40 <dbl>, sample41 <dbl>,
#> # sample42 <dbl>, sample43 <dbl>, sample44 <dbl>, sample45 <dbl>,
#> # sample46 <dbl>, sample47 <dbl>, sample48 <dbl>, sample49 <dbl>