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 given the following data Group 1: Internship Group 2: Co-op Group 3: Work Study 10.5 14.25 14.25 12 15.25 8.75 10 15.25 15.75 11 15.75 10.5 16.25 14 9.75 10.75 12.5 15 10.75 14.25 15.75 16.25 13 14.25 12.25 15.5 9.5 8.75 17 12.5 For this study, we should use ??? 2. Your friend Valerie helped you with the null and alternative hypotheses... H0: μ1=μ2=μ3H0: μ1=μ2=μ3 H1:H1: At least one of the mean is different from the others. 3. The test-statistic for this data = ??? (Please show your answer to 3 decimal places.) 4. The p-value for this sample = ???? (Please show your answer to 4 decimal places.) 5. The p-value is ? αα -less than (or equal to) alpha -greater than alpha 6. Base on this, we should ? hypothesis -reject the null hypothesis -accept the alternative hypothesis -accept the null hypothesis -fail to reject the null hypothesis 7. As such, the final conclusion is that... Base 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. Base 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.

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Description: 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

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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 given the following data

Group 1: Internship	Group 2: Co-op	Group 3: Work Study
10.5	14.25	14.25
12	15.25	8.75
10	15.25	15.75
11	15.75	10.5
16.25	14	9.75
10.75	12.5	15
10.75	14.25	15.75
16.25	13	14.25
12.25	15.5	9.5
8.75	17	12.5

For this study, we should use ???

2. Your friend Valerie helped you with the null and alternative hypotheses...
H0: μ1=μ2=μ3H0: μ1=μ2=μ3
H1:H1: At least one of the mean is different from the others.

3. The test-statistic for this data = ??? (Please show your answer to 3 decimal places.)

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

5. The p-value is ? αα

-less than (or equal to) alpha

-greater than alpha

6. Base on this, we should ? hypothesis

-reject the null hypothesis

-accept the alternative hypothesis

-accept the null hypothesis

-fail to reject the null hypothesis

7. As such, the final conclusion is that...

Base 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.
Base 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.

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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