Find the area under the standard normal distribution curve Assessing NormalityMany times in statistics it is necessary to see if a set of data values is approximately normallydistributed. There are special techniques that can be used. One technique is to draw ahistogram for the data and see if it is approximately bell-shaped. (Note: It does not have tobe exactly symmetric to be bell-shaped.)The numbers of branches of the 50 top libraries are shown.33678480779759623742365418121933492425229.2431171521242921211319192222304122182026331414162210162426 19. Between z = –1.46 and z = -1.98

The z-scores are -1.46 and -1.98.

Answered: Find the area under the standard normal…

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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Find the area under the standard normal distribution curve

Assessing Normality
Many times in statistics it is necessary to see if a set of data values is approximately normally
distributed. There are special techniques that can be used. One technique is to draw a
histogram for the data and see if it is approximately bell-shaped. (Note: It does not have to
be exactly symmetric to be bell-shaped.)
The numbers of branches of the 50 top libraries are shown.
33
67
84
80
77
97
59
62
37
42
36
54
18
12
19
33
49
24
25
22
9.
24
31
17
15
21
24
29
21
21
13
19
19
22
22
30
41
22
18
20
26
33
14
14
16
22
10
16
24
26

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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