The following three independent random samples are obtained from three normally distributed populations with equal variance. The dependent variable is starting hourly wage, and the groups are the types of position (internship, co-op, work study).We are testing the claim that the starting salaries for new college graduate are different depending on the positions at α=0.05α=0.05. The sample data is in the table below.Group 1: InternshipGroup 2: Co-opGroup 3: Work Study131013.7513.511.2515.251511.7515.510.7511.7513.2511.75141413.7511.518.2515.7516.514.2511.759.512.5For this study, we should use Your friend Zoe helped you with the null and alternative hypotheses...H0: μ1=μ2=μ3H0: μ1=μ2=μ3H1:H1: At least one of the means is different from the others.The test-statistic for this data = (Please show your answer to 3 decimal places.) The p-value for this sample = (Please show your answer to 4 decimal places.) The p-value is αα We should . The conclusion is that...Based on the sample data, there is not sufficient evidence to conclude that the starting salaries for a new college graduate are the same for the positions at αα=0.05.Based on the sample data, there is sufficient evidence to conclude the claim that the starting salaries for new college graduate are different depending on the positions at αα = 0.05.Based on the sample data, there is not sufficient evidence to conclude the claim that the starting salaries for new college graduate are different depending on the positions at αα = 0.05.Based on the sample data, there is sufficient evidence to conclude that the starting salaries for a new college graduate are the same for the positions at αα=0.05.

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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 following three independent random samples are obtained from three normally distributed populations with equal variance.

The dependent variable is starting hourly wage, and the groups are the types of position (internship, co-op, work study).

We are testing the claim that the starting salaries for new college graduate are different depending on the positions at α=0.05α=0.05. The sample data is in the table below.

Group 1: Internship	Group 2: Co-op	Group 3: Work Study
13	10	13.75
13.5	11.25	15.25
15	11.75	15.5
10.75	11.75	13.25
11.75	14	14
13.75	11.5	18.25
15.75	16.5	14.25
11.75	9.5	12.5

For this study, we should use

Your friend Zoe helped you with the null and alternative hypotheses...
H0: μ1=μ2=μ3H0: μ1=μ2=μ3
H1:H1: At least one of the means is different from the others.
The test-statistic for this data = (Please show your answer to 3 decimal places.)

The p-value for this sample = (Please show your answer to 4 decimal places.)

The p-value is αα

We should .

The conclusion is that...
- Based on the sample data, there is not sufficient evidence to conclude that the starting salaries for a new college graduate are the same for the positions at αα=0.05.
- Based on the sample data, there is sufficient evidence to conclude the claim that the starting salaries for new college graduate are different depending on the positions at αα = 0.05.
- Based on the sample data, there is not sufficient evidence to conclude the claim that the starting salaries for new college graduate are different depending on the positions at αα = 0.05.
- Based on the sample data, there is sufficient evidence to conclude that the starting salaries for a new college graduate are the same for the positions at αα=0.05.

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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