Heights of WOMEN in the U.S. are normally distributed. Recent information shows: Adult women height: µ = 63.8 inches with σ = 2.8 inches. From the given frequency distribution, we see that _____ of the 52 women in our RCCC sample were between 62 and 69 inches tall, which would be approximately _____ % (0 decimal places). This is __________ percentage points _______________ (above or below) that of the U.S. population. (Note: Include 62 and 69 inches.) +Sample of RCCC Women's Heights - Spring 2022Height (in inches)Frequency6148771237CC388688REN62646566676970717220101

Solution-: Given: μ=63.8, σ=2.8 Sample of RCCC women's heights Heigh (inches) Frequency 61 4…

Answered: Heights of WOMEN in the U.S. are…

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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Heights of WOMEN in the U.S. are normally distributed. Recent information shows:

Adult women height: µ = 63.8 inches with σ = 2.8 inches.

From the given frequency distribution, we see that _____ of the 52 women in our RCCC sample were between 62 and 69 inches tall, which would be approximately _____ % (0 decimal places). This is __________ percentage points _______________ (above or below) that of the U.S. population. (Note: Include 62 and 69 inches.)

+Sample of RCCC Women's Heights - Spring 2022
Height (in inches)
Frequency
61
4
8
7
7
12
3
7
CC388688REN
62
64
65
66
67
69
70
71
72
2
0
1
0
1

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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