How to generate standard normal random numbers in R?
A standard normal distribution is the type of distribution that has mean equals to zero with standard deviation 1. If we want to generate standard normal random numbers then rnorm function of R can be used but need to pass the mean = 0 and standard deviation = 1 inside this function.
Example
Live Demo
rnorm(10,0,1)
Output
[1] 0.6936607 -0.7967657 -2.7544428 0.2688767 0.5278463 -1.5387568
[7] 1.1716632 -1.5033895 0.8112929 -1.0101065
Example
Live Demo
rnorm(50,0,1)
Output
[1] 2.58246666 -0.53083341 -0.57343343 1.08172756 1.30341849 -0.07440422
[7] -0.41869305 -0.96227706 -0.46899119 1.55428279 0.09162738 -0.96027221
[13] -0.84735327 -1.74949782 0.58541758 0.23117630 0.47402479 -0.72453853
[19] 0.07171564 1.13088794 0.18735157 0.25091758 -1.34728315 -0.39768159
[25] -0.38109955 -0.34019286 -1.51778561 -0.92222239 -1.22798041 -0.77350032
[31] -1.65852274 0.51227977 0.83822730 0.45359267 0.49714674 -1.47674552
[37] -0.01242228 1.60937112 0.38869615 1.73720338 0.56832087 -0.35619856
[43] -1.74371897 -0.77162373 -1.80142363 -0.92801065 0.92791947 0.14078622
[49] -1.55200961 -0.06995120
Example
Live Demo
rnorm(60,0,1)
Output
[1] -0.98030635 0.14934486 -1.55025640 0.80780101 -0.54240515 0.14488726
[7] 2.89290245 1.10729520 0.08050478 -0.44497057 1.10941494 1.74939247
[13] 0.84032675 0.47427879 0.11898992 1.85356655 0.19312780 -0.47810793
[19] 2.36569993 -0.45530246 -0.81494824 -1.99941347 -0.50359976 0.55592840
[25] 1.14048452 -1.02259883 -1.17629055 1.48930583 1.76136612 0.70749370
[31] 0.88976803 0.87302066 -0.90594396 -0.92584519 -0.57771767 -2.01680635
[37] 1.25990880 0.87272304 3.86728923 0.48660167 2.12238845 -1.23884756
[43] -0.29534035 -1.66654062 -0.92580904 0.46701435 -0.27171548 -0.79118171
[49] -1.87119180 -1.43572885 3.60672069 0.58631139 -0.38245860 0.62229426
[55] -0.54297322 -2.39866511 -1.91755583 -0.61459590 0.11865738 0.65653693
Example
Live Demo
rnorm(80,0,1)
Output
[1] -0.21167734 1.00334018 0.58986878 -1.15025242 0.83748340 0.04415646
[7] 0.21006101 -0.35285172 -0.53306794 -0.31683124 -0.15284674 1.72136890
[13] 0.67868984 -0.40103797 0.19409371 -0.31236848 1.08174032 0.82741254
[19] 1.52301592 0.92592501 -1.13193294 -0.52651889 -0.22310016 -0.93938644
[25] 0.27894221 -2.89894569 0.36546350 0.84345631 -0.81706708 0.18261437
[31] -0.69591250 1.09539577 -1.15864497 -0.22639388 -0.32866906 -1.12182835
[37] -0.08435003 1.81382691 0.04255180 -0.32941539 2.64070059 1.56935548
[43] -0.24635038 0.62292947 1.05232124 0.67012389 0.91400357 0.26348570
[49] -0.35494585 1.09602375 -1.39164787 -0.36638726 1.76550599 -0.22423221
[55] -0.33138915 -0.66652623 -0.50509947 -0.93338252 -2.70014038 -0.52016919
[61] 0.80396082 0.75912405 0.52966924 0.76088675 0.87390249 0.19404944
[67] -0.94092779 -1.20741440 -1.28536191 0.03052385 -2.23973254 -0.39531601
[73] -0.84322501 0.78849127 1.70032152 1.11591005 -1.15304534 -1.23219567
[79] 0.91807504 1.21157462
Example
Live Demo
rnorm(100,0,1)
Output
[1] -0.60163722 0.62726820 -0.78769462 0.72244706 -0.57654069 0.21386083
[7] -0.53096986 0.34563279 -0.97023650 -0.94702500 -0.37624883 0.44073439
[13] 0.51851495 -1.93362586 0.74274197 -0.81861024 -0.49963242 1.45553031
[19] -0.47880775 -0.23169624 0.46348261 -1.19764668 0.77737123 -0.50783209
[25] -1.58899290 0.50528381 1.89222336 -0.57809997 0.05806867 1.16785099
[31] -1.06614535 0.61556520 -0.83564718 -1.02615977 0.89271898 0.53811493
[37] -0.54849449 -0.62497474 0.25675859 0.70320768 0.05848728 0.78376690
[43] 0.44276061 -0.58697558 -0.59758547 1.22975543 1.46945195 -0.79496156
[49] -0.58237963 0.16137738 0.22260587 0.45833685 -0.17046269 0.44890726
[55] -0.15563031 0.73221957 -1.97896622 -1.47629166 -2.02214096 -0.96495535
[61] 0.63474420 1.34149420 -0.91755563 0.35488624 0.01262576 -0.34079663
[67] 0.07963539 0.88896173 1.75045613 -0.08678552 0.19245374 1.32575165
[73] 1.41738151 -1.35060833 0.63737697 0.33369705 1.27021960 1.00779108
[79] -1.19586882 0.72829141 -0.09938002 -0.79827963 -1.20575102 -1.09457152
[85] 0.66310803 -0.41086839 -0.50120916 0.02167787 0.60022806 2.94091060
[91] -0.39845012 0.82483674 -2.72699869 -0.48183377 0.57821380 -0.85565220
[97] 2.55905507 0.24447168 0.53042496 -0.31205488
Published on 07-Dec-2020 10:24:03
