- Trending Categories
Data Structure
Networking
RDBMS
Operating System
Java
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
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
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
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
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
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
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
- Related Articles
- Generate random numbers following a normal distribution in C/C++
- How to generate a normal random vector using the mean of a vector in R?
- Generate random numbers by giving certain mean and standard deviation in Excel
- How to generate large random numbers in Java?
- How to generate Bernoulli random variable in R?
- How to generate random numbers between two numbers in JavaScript?
- How does Python generate random numbers?
- How to generate non-repeating random numbers in Python?
- Generate random numbers in Arduino
- Java program to generate random numbers
- How to use Python Numpy to generate Random Numbers?
- How to generate random numbers with sequence and store in a data frame column in R?
- How to generate 5 random numbers in MySQL stored procedure?
- Generate pseudo-random numbers in Python
- Generate Random Integer Numbers in Java

Advertisements