Answer:
A) attached below
B) mean value = 67.755, std = 26.871
C) IQR( interquartile range ) = 37
Explanation:
<u>A) Construct a histogram for the data and use it to evaluate the validity of normality assumption </u>
<em>Using Minitab to construct the Histogram</em> from the shape of the Histogram we can see that the Normality assumption is valid because the shape is fairly symmetric
screenshot of Histogram is attached below
<u>B) Obtain the mean and standard deviation for the data and use these statistics to evaluate the validity of the normality assumption.</u>
still using Minitab to determine the std and mean values
mean value = 67.755, std = 26.871
Next : find the percentage of the observation that lie within 1,2 and 3 std from the mean
For one(1) std from the mean the interval = ( 40.884, 94.626 )
percentage of observation = 665 / 992 = 67.04
For two(2) std from the mean; The interval = ( 14.013 , 121.497 )
percentage of observation = 946 / 992 = 95.36%
For three(3) std from the mean ; The interval = ( -12.858, 148.368 )
percentage of observations = 991 / 992 = 99.90%
The percentages from the above calculations indicates the validity of the normality assumption
<u>C) Obtain the interquartile rage for the data and use these statistics to evaluate the validity of the normality assumption</u>
using MINITAB
since the data are assumed Normal; Ratio = ![\frac{IQR}{S} = 1.3](https://tex.z-dn.net/?f=%5Cfrac%7BIQR%7D%7BS%7D%20%3D%201.3)
std (s) = 26.871, IQR( interquartile range ) = 37
Next check if IQR / S will be = 1.3
= 37 / 26.871 = 1.377 ( This validates the normality assumption )