Multiplying random value by variance + motivation

Click For Summary
SUMMARY

To transform a random variable to follow a specific probability distribution function (pdf), one must multiply the standard normal variable by the standard deviation, which is the square root of the variance of the desired pdf. This operation ensures that the resulting random variable retains the same distribution type while adjusting its variance. The discussion emphasizes the importance of understanding the relationship between standard deviation and variance in the context of probability distributions.

PREREQUISITES
  • Understanding of probability distribution functions (pdf)
  • Knowledge of standard normal distribution
  • Familiarity with variance and standard deviation concepts
  • Basic statistics and random variable theory
NEXT STEPS
  • Study the properties of different probability distribution functions (pdfs)
  • Learn about the Central Limit Theorem and its implications for random variables
  • Explore the concept of transformation of random variables in statistics
  • Investigate the application of variance in statistical modeling and simulations
USEFUL FOR

Statisticians, data scientists, and anyone involved in probabilistic modeling or statistical analysis will benefit from this discussion.

JamesGoh
Messages
140
Reaction score
0
Just a quick question.

If you want any value to follow a particular probability distribution function (pdf), do you have to multiply that value by the variance of the desired pdf ?
 
Physics news on Phys.org
JamesGoh said:
Just a quick question.

If you want any value to follow a particular probability distribution function (pdf), do you have to multiply that value by the variance of the desired pdf ?

What is the probability distribution of the given random variable? If it starts out as standard normal, you can multiply it by the standard deviation (square root of variance) to get a normally distributed r.v. with the desired variance. In general by multiplying by the s.d. you will get a r.v. with the same kind of distribution.
 
thanks for that

Initially, I was concerned with a value following any pdf distribution being multiplied by a specific pdf variance
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
440
  • · Replies 42 ·
2
Replies
42
Views
6K
Replies
5
Views
6K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 28 ·
Replies
28
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 14 ·
Replies
14
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 9 ·
Replies
9
Views
3K