Answered: Part 1 Trials in an experiment with a…

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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Part 1

Trials in an experiment with a polygraph include 96 results that include 23 cases of wrong results and 73
cases of correct results. Use a 0.01 significance level to test the claim that such polygraph results are correct less than 80% of the time. Identify the null hypothesis, alternative hypothesis, test statistic, P-value, conclusion about the null hypothesis, and final conclusion that addresses the original claim. Use the P-value method. Use the normal distribution as an approximation of the binomial distribution.

Let p be the population proportion of correct polygraph results. Identify the null and alternative hypotheses. Choose the correct answer below.

H0:

p=0.20

H1:

p>0.20

H0:

p=0.80

H1:

p<0.80

H0:

p=0.80

H1:

p≠0.80

H0:

p=0.80

H1:

p>0.80

H0:

p=0.20

H1:

p≠0.20

H0:

p=0.20

H1:

p<0.20

Part 2

The test statistic is

z=enter your response here.

(Round to two decimal places as needed.)

Part 3

The P-value is

enter your response here.

(Round to four decimal places as needed.)

Part 4

Identify the conclusion about the null hypothesis and the final conclusion that addresses the original claim.

▼

Reject

Fail to reject

H0.

There

▼

is not

sufficient evidence to support the claim that the polygraph results are correct less than

80%

of the time.

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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