Say that we have two datapoints x and y. Both x and y are independently normally distributed with variance 1. The mean of x is µx and the mean of y is µy.1. You have a null hypothesis of µx= µy. You will reject if |x − y| > 2. What is the type I error rate of this test? 2. You have a null hypothesis of µx= µy. You will reject if |x − y| > 2. If µx - µy = 10, what is the type II error rate of this test? Say that we have two datapoints x and y. Both x and y are independently normally distributedwith variance 1. The mean of x is µ, and the mean ofis ly.1. You have a null hypothesis of ug = ly. You will reject if |x – y| > 2. Whatis the type I error rate of this test?You have a null hypothesis of He = Hy. You will reject if |x – y| > 2. If10, what is the type II error rate of this test?2.Hx - Hy =

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Say that we have two datapoints x and y. Both x and y are independently normally distributed with variance 1. The mean of x is µ_x and the mean of y is µ_y.

1. You have a null hypothesis of µ_x= µ_y. You will reject if |x − y| > 2. What is the type I error rate of this test?

2. You have a null hypothesis of µ_x= µ_y. You will reject if |x − y| > 2. If µ_x- µ_y= 10, what is the type II error rate of this test?

Say that we have two datapoints x and y. Both x and y are independently normally distributed
with variance 1. The mean of x is µ, and the mean of
is ly.
1. You have a null hypothesis of ug = ly. You will reject if |x – y| > 2. What
is the type I error rate of this test?
You have a null hypothesis of He = Hy. You will reject if |x – y| > 2. If
10, what is the type II error rate of this test?
2.
Hx - Hy =

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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