Marginal PDF for Sum of Squares: Identifying Distribution and Calculation Method

Since the sum of i.i.d. normal distributions is also a normal distribution, we can rewrite the expression as $$\sum_{i=1}^n \left(\frac{X_i-\overline X}{\sigma}\right)^2$$.If we define $Z_i = \frac{X_i-\overline X}{\sigma}$, then $Z_i \sim N(0,1)$.Now, we can rewrite the expression as $$\sum_{i=1}^n (Z_i)^2 = \chi_n^2$$.Therefore, the marginal pdf of $$\sum_{i=1}^n (X_i-\overline{X})^2$$ is $$f_{\
  • #1
Fermat1
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Let $$X_1,\dots,X_n$$ be i.i.d $$N(\mu,\sigma^2)$$. What is the marginal pdf of $$\sum_{i=1}^n (X_i-\overline{X})^2$$.

I'm guessing it's some sort of chi square distribution but how to find this I am unsure. Thanks
 
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  • #2
Fermat said:
Let $$X_1,\dots,X_n$$ be i.i.d $$N(\mu,\sigma^2)$$. What is the marginal pdf of $$\sum_{i=1}^n (X_i-\overline{X})^2$$.

I'm guessing it's some sort of chi square distribution but how to find this I am unsure. Thanks

The chi-square distribution is defined as \(\displaystyle \chi_n^2 = \sum_{i=1}^n Y_i^2\) where $Y_i \sim N(0,1)$.
We need to rewrite the expression to standard normal distributions to relate it to the chi-square distribution.
The first step has already been done, since $X_i-\overline X \sim N(0,\sigma^2)$.
 

1. What is a marginal pdf?

A marginal pdf, or probability density function, is a statistical tool used to determine the probability of a continuous random variable falling within a certain range of values. It represents the distribution of one variable, while holding all other variables constant.

2. How is a marginal pdf different from a joint pdf?

A joint pdf represents the probability of multiple variables occurring simultaneously, while a marginal pdf represents the probability of a single variable occurring without taking into account the other variables. In other words, a marginal pdf is obtained by integrating a joint pdf over all other variables except the one of interest.

3. What is the relationship between a marginal pdf and a conditional pdf?

A conditional pdf represents the probability of a certain event occurring given that another event has already occurred. The marginal pdf can be derived from the conditional pdf by setting the condition to be the entire sample space.

4. How is a marginal pdf used in statistical analysis?

A marginal pdf is used to calculate probabilities and make predictions about a single variable in a multivariate system. It can also be used to determine the expected value, variance, and other summary statistics of the variable of interest.

5. Can a marginal pdf be used for discrete random variables?

Yes, a marginal pdf can be used for both continuous and discrete random variables. For discrete variables, the marginal pdf is also known as a marginal probability mass function.

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