Fill in the blank space with TRUE or FALSE. 2 If X₁,...,. 1,..., Xn ~ N(μ, 0²) are i.i.d, then E(X²) = μ² + ₁ n If X₁,..., Xn~ N(0, 1) are i.i.d, then E(nX²) = 1 If X₁,..., Xn~ N(0, 1) are i.i.d with n = 25, then P(-25 ≤X ≤ 30) = 0 If X ~ N(0, 1), then X² is also normally distributed If X~ N(0, 1) and Y~ N(0, 1) are independent, then X+Y~ N(0, 1)
Fill in the blank space with TRUE or FALSE. 2 If X₁,...,. 1,..., Xn ~ N(μ, 0²) are i.i.d, then E(X²) = μ² + ₁ n If X₁,..., Xn~ N(0, 1) are i.i.d, then E(nX²) = 1 If X₁,..., Xn~ N(0, 1) are i.i.d with n = 25, then P(-25 ≤X ≤ 30) = 0 If X ~ N(0, 1), then X² is also normally distributed If X~ N(0, 1) and Y~ N(0, 1) are independent, then X+Y~ N(0, 1)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Hello, I have a homework and this part I don't understand, May you help me? Please

Transcribed Image Text:Fill in the blank space with TRUE or FALSE.
●
●
●
If X₁,..., Xn ~ N(μ, o²) are i.i.d, then E(X²
If X₁,..., Xn~ N(0, 1) are i.i.d, then E(nX²) = 1
=
~
n
If X₁,..., Xn
If X ~ N(0, 1), then X² is also normally distributed
If X ~ N(0, 1) and Y ~ N(0, 1) are independent, then X + Y ~ N(0, 1)
The sample standard deviation is an unbiased estimator of the population standard deviation
If a distribution is symmetric, then the mean, median and mode may coincide
X
If X binomial (n, p), then p
is an unbiased estimator of p
N(0, 1) are i.i.d with n = 25, then P(-25 ≤ X ≤ 30) = 0
==
n
If X1,..., Xn Poisson(X) are i.i.d, then E(X²) = x²
If X₁,.
Xn~
Exponential (A) are i.i.d, then √ π ( XX − 1) ~ N(0, 1)
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