Chi Square Distribution Problem

In summary, the conversation discusses finding the distribution of n(Sample Mean - μ)2/σ2 for a normal distribution. The solution involves using the normal distribution of the sample mean ~ N(μ,σ2/n) and converting it into a z-score, which results in a chi square distribution with n degrees of freedom. The final step is to find the distribution of Z^2.
  • #1
Nexttime35
46
1

Homework Statement


Suppose that X has normal distribution. Find the distribution of n(Sample Mean - μ)22.

The Attempt at a Solution


I honestly have no idea where to begin with this problem. Any ideas?
 
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  • #2
Tell us what you know about this problem. It must be homework for something you've been learning in class.
 
  • #3
Well I know that the Sample mean has a normal distribution ~ N(μ,σ2/n), which I think is useful to solve this problem. Now, I am confused about how to use this normal distribution for the sample mean to solve the problem. Any thoughts, using this idea?
 
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  • #4
LCKurtz said:
If ##\bar X \sim N(\mu, \frac {\sigma^2}{n})## what is the distribution of$$
Z=\frac{\bar X -\mu}{\frac\sigma {\sqrt n}}$$Once you answer that, you need to work out the distribution of ##Z^2##.
 
  • #5
Hi LCKurtz,

Thanks for the help. I am wondering where you got this equation from? I know it's the z-score, converting the sample mean into the z-score, but how did you come up with the equation? Thanks.
 
  • #6
Actually I believe I know where this comes from.

the Sum from i=1 to n of Zi2 = the Sum from i=1 to n of ((Xi-μ)/σ)2 = chi square distribution with n degrees of freedom.
 
  • #7
So, would the distribution of this be N(0,n)?
 
  • #8
Nexttime35 said:

Homework Statement


Suppose that X has normal distribution. Find the distribution of n(Sample Mean - μ)22.

Nexttime35 said:
Hi LCKurtz,

Thanks for the help. I am wondering where you got this equation from? I know it's the z-score, converting the sample mean into the z-score, but how did you come up with the equation? Thanks.

Now you are confusing me. It is your question asking for the distribution of$$
\frac {n(\bar X - \mu)^2}{\sigma^2} =\frac{(\bar X - \mu)^2}{(\frac \sigma {\sqrt n})^2}$$
So if ##Z = \frac{(\bar X - \mu)}{\frac \sigma {\sqrt n}}##, you know ##Z\sim n(0,1)## and your problem is to find the distribution of ##Z^2##.
 

1. What is a Chi Square Distribution Problem?

A Chi Square Distribution Problem is a statistical test used to determine if there is a significant difference between expected and observed data. It is often used to analyze categorical data and test for independence or goodness of fit.

2. How do you calculate a Chi Square value?

To calculate a Chi Square value, you need to first determine the expected values for each category. Then, you take the observed values and subtract the expected values, square the result, and divide by the expected value. Repeat this for each category and add all the values together to get the Chi Square value.

3. What does a high or low Chi Square value indicate?

A high Chi Square value indicates a significant difference between the expected and observed data, meaning that there is likely a relationship between the variables being tested. A low Chi Square value indicates that there is no significant difference and the variables are likely independent or fit the expected distribution.

4. What is the null hypothesis in a Chi Square Distribution Problem?

The null hypothesis in a Chi Square Distribution Problem is that there is no significant difference between the observed and expected data. It assumes that any differences are due to chance and that the variables being tested are independent.

5. What other statistical tests are similar to Chi Square?

Other statistical tests that are similar to Chi Square include ANOVA (Analysis of Variance) and t-tests, which are used to compare means of continuous variables. However, Chi Square is specifically designed for categorical data and is more appropriate for analyzing relationships between non-numerical variables.

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