The amount of time taken by students to finish an online test was measured and the lecturer suspects the time follows a normal distribution. The time taken by 54 students to finish the exam was collected as shown in the numeric frequency table.intervals number of students (f0)below 701170 -80 2480-9013above 906total54The mean was calculated to be 77.6 and standard deviation was 9.15.Use the chi-square goodness of fit test to test, at 1% level of significance that the finishing time follows a normal distribution with mean 77.6 and standard deviation of 9.15.

The chi-square goodness of fit test can be used to determine whether a sample distribution follows…

Answered: The amount of time taken by students to…

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 amount of time taken by students to finish an online test was measured and the lecturer suspects the time follows a normal distribution. The time taken by 54 students to finish the exam was collected as shown in the numeric frequency table.

intervals	number of students (f0)
below 70	11
70 -80	24
80-90	13
above 90	6
total	54

The mean was calculated to be 77.6 and standard deviation was 9.15.

Use the chi-square goodness of fit test to test, at 1% level of significance that the finishing time follows a normal distribution with mean 77.6 and standard deviation of 9.15.

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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