The following questions refer to the standard normal distribution.A. The standard normal distribution is a symmetric curve with a mean of 0. TrueFalse B. The z score corresponding to a number below the mean is postive. TrueFalse C. The area to the left of z = 0 is negative. TrueFalse D. Which of the following is not true about the standard normal curve? It's continuous.It's uniform.It's bell shaped. E. What is the total area under a normal curve? 1can not be determinedinfinite F. If P(-c < z < c) = 0.88, then P(z > c) = 0.06 TrueFalse G. If P(z > c) = 0.2, what is P(z < -c) ?

The objective of the question is to test the understanding of the standard normal distribution and…

Answered: The following questions refer to the…

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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The following questions refer to the standard normal distribution.

A. The standard normal distribution is a symmetric curve with a mean of 0.

True
False

B. The z score corresponding to a number below the mean is postive.

True
False

C. The area to the left of z = 0 is negative.

True
False

D. Which of the following is not true about the standard normal curve?

It's continuous.
It's uniform.
It's bell shaped.

E. What is the total area under a normal curve?

1
can not be determined
infinite

F. If P(-c < z < c) = 0.88, then P(z > c) = 0.06

True
False

G. If P(z > c) = 0.2, what is P(z < -c) ?

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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