Answered: that we want to construct a confidence…

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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Question

Assume that we want to construct a confidence interval. Do one of the following, as appropriate: (a) find the critical value

tα/2,

(b) find the critical value

zα/2,

or (c) state that neither the normal distribution nor the t distribution applies.

The confidence level is

95%,

is not known, and the histogram of

player salaries (in thousands of dollars) of football players on a team is as shown.

040008000120001600020000010203040Salary (thousands of dollars)Frequency

A histogram has a horizontal axis labeled "Salary (thousands of dollars)" from below 0 to above 20000 in increments of 2000 and a vertical axis labeled "Frequency" from 0 to 40 in increments of 10. The histogram contains vertical bars of width 2000, where one vertical bar is centered over each of the horizontal axis tick marks. The heights of the vertical bars are as follows, where the salary is listed first and the height is listed second: 0, 34; 2000, 12; 4000, 2; 6000, 4; 8000, 3; 10000, 3; 12000, 0; 14000, 0; 16000, 0; 18000, 0; 20000, 1.

Select the correct choice below and, if necessary, fill in the answer box to complete your choice.

tα/2=enter your response here

(Round to two decimal places as needed.)

zα/2=enter your response here

(Round to two decimal places as needed.)

Neither the normal distribution nor the t distribution applies.

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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