Finding Constants for a Gaussian PDF

In summary, the question asks to find the constants a and b so that the random variable y = aX + b has a Gaussian PDF with mean m' and standard deviation \sigma'. The solution involves using the equations E(aX+b) = aE(X) + b = \mu_1 and Var(aX+b) = \sigma^2 to find appropriate values for a and b. The relationship between m' and \sigma' is also mentioned in the question.
  • #1
ahamdiheme
26
0

Homework Statement



The exam grades in a certain class have a Gaussian PDF with mean m and standard deviation [tex]\sigma[/tex]. Find the constants a and b so that the random variable y=aX+b has a Gaussian PDF with mead m' and standard deviation [tex]\sigma[/tex]'.

Homework Equations





The Attempt at a Solution


I really do not know where to go from here, i need a heads-up.
Thanks
 
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  • #2
Is [tex] aX + b [/tex] to have a different mean but same standard deviation? I'm not entirely clear from your post.

You do know that if [tex] X [/tex] is Gaussian then [tex] aX + b [/tex] is also Guassian for any choices of [tex] a \ne 0 \text{ and real }b [/tex], right, so you don't need to show that part.

If [tex] \mu_1 [/tex] is supposed to be the new mean, then

[tex]
E(aX+b) = aE(X) + b = \mu_1
[/tex]

The other condition requires you to work with the variances: If the standard deviation doesn't change then you know that

[tex]
Var(aX+b) = \sigma^2
[/tex]

Simplifying and working with these equations will let you find appropriate values for [tex] a, b [/tex]. Play with them.
 
  • #3
no the new deviation is [tex]\sigma'[/tex]
 
  • #4
I'm not sure what you mean by saying "the new standard deviation is [tex] \sigma' [/tex]

Is it simply that

[tex]
\sigma' = \sqrt{Var(aX+b)}
[/tex]
 
  • #5
y=aX+b has a Gaussian PDF with mean m' and standard deviation '

that relationship, i know. the m' goes with [tex]\sigma'[/tex].
Hope u understand what the question says now. It seems a little confusing but that's the exact way the textbook put it. Thank you
 

Related to Finding Constants for a Gaussian PDF

1. What is a Gaussian PDF?

A Gaussian PDF (Probability Density Function) is a mathematical function that describes the probability distribution of a continuous random variable. It is also known as a normal distribution and is characterized by a bell-shaped curve.

2. Why is it important to find constants for a Gaussian PDF?

Constants for a Gaussian PDF, such as the mean and standard deviation, help to define the shape and location of the distribution. They also allow us to calculate probabilities and make predictions about the data being studied.

3. How do you find the mean and standard deviation for a Gaussian PDF?

The mean is calculated by taking the average of all the data points in the distribution. The standard deviation is a measure of how spread out the data is from the mean, and is calculated by taking the square root of the variance. Both can also be estimated using statistical methods.

4. Can constants for a Gaussian PDF change?

Yes, constants for a Gaussian PDF can change if the underlying data changes. For example, if there is a shift in the mean or an increase in the standard deviation, the constants for the Gaussian PDF will also change.

5. What are some applications of finding constants for a Gaussian PDF?

Finding constants for a Gaussian PDF is used in various fields such as statistics, physics, engineering, and finance. It is commonly used in data analysis and modeling to understand and make predictions about real-world phenomena.

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