BUS 308 Week 3 Assignment

BUS 308 Week 3 Assignment in EXCEL (A+ Grade Assured, Latest Data)

Paired T-test and ANOVA
Week 3

Week 3	Paired T-test and ANOVA
	For this week's work, again be sure to state the null and alternate hypotheses and use alpha = 0.05 for our decision
	value in the reject or do not reject decision on the null hypothesis.

1	Many companies consider the grade midpoint to be the "market rate" - the salary needed to hire a new employee.											Salary	Midpoint	Diff
	Does the company, on average, pay its existing employees at or above the market rate?
	Use the data columns at the right to set up the paired data set for the analysis.

	Null Hypothesis:
	Alt. Hypothesis:

		Statistical test to use:



















		What is the p-value:
	Is P-value < 0.05 (one tail test) or 0.25 (two tail test)?
What else needs to be checked on a 1-tail test in order to reject the null?
		Do we REJ or Not reject the null?
If the null hypothesis was rejected, what is the effect size value:
	If calculated, what is the meaning of effect size measure:

	Interpretation of test results:



Let's look at some other factors that might influence pay - education(degree) and performance ratings.

2	Last week, we found that average performance ratings do not differ between males and females in the population.
	Now we need to see if they differ among the grades. Is the average performace rating the same for all grades?
	(Assume variances are equal across the grades for this ANOVA.)							Here are the data values sorted by grade level.
	The rating values sorted by grade have been placed in columns I - N for you.							A	B	C	D	E	F
	Null Hypothesis:	Ho: means equal for all grades						90	80	100	90	85	70
	Alt. Hypothesis:	Ha: at least one mean is unequal						80	75	100	65	100	100
	Place B17 in Outcome range box.							100	80	90	75	95	95
								90	70	80	90	55	95
								80	95	80	95	90	95
								85	80			95	95
								65	90			90
								70				75
								95				95
								60				90
								90				95
								75				80
								95
								90
								100







	Interpretation of test results:
					What is the p-value:	0.57	If the ANVOA was done correctly, this is the p-value shown.
					Is P-value < 0.05?
					Do we REJ or Not reject the null?
	If the null hypothesis was rejected, what is the effect size value (eta squared):
					Meaning of effect size measure:

					What does that decision mean in terms of our equal pay question:


3	While it appears that average salaries per each grade differ, we need to test this assumption.
	Is the average salary the same for each of the grade levels?
	Use the input table to the right to list salaries under each grade level.
	(Assume equal variance, and use the analysis toolpak function ANOVA.)
	Null Hypothesis:							If desired, place salaries per grade in these columns
	Alt. Hypothesis:							A	B	C	D	E	F

	Place B51 in Outcome range box.



















	Note: Sometimes we see a p-value in the format of 3.4E-5; this means move the decimal point left 5 places. In this example, the p-value is 0.000034
					What is the p-value:
					Is P-value < 0.05?
					Do we REJ or Not reject the null?
		If the null hypothesis was rejected, calculate the effect size value (eta squared):
		If calculated, what is the meaning of effect size measure:

					Interpretation:

4	The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results.
	Note: These values are not the same as the data the assignment uses. The purpose of this question is to analyze the result of a 2-way ANOVA test rather than directly answer our equal pay question.
		BA	MA		Ho: Average compas by gender are equal
	Male	1.017	1.157		Ha: Average compas by gender are not equal
		0.870	0.979		Ho: Average compas are equal for each degree
		1.052	1.134		Ha: Average compas are not equal for each degree
		1.175	1.149		Ho: Interaction is not significant
		1.043	1.043		Ha: Interaction is significant
		1.074	1.134
		1.020	1.000		Perform analysis:
		0.903	1.122
		0.982	0.903		Anova: Two-Factor With Replication
		1.086	1.052
		1.075	1.140		SUMMARY	BA	MA	Total
		1.052	1.087		Male
	Female	1.096	1.050		Count	12	12	24
		1.025	1.161		Sum	12.349	12.9	25.249
		1.000	1.096		Average	1.02908333	1.075	1.052042
		0.956	1.000		Variance	0.00668645	0.006519818	0.006866
		1.000	1.041
		1.043	1.043		Female
		1.043	1.119		Count	12	12	24
		1.210	1.043		Sum	12.791	12.787	25.578
		1.187	1.000		Average	1.06591667	1.065583333	1.06575
		1.043	0.956		Variance	0.00610245	0.004212811	0.004933
		1.043	1.129
		1.145	1.149		Total
					Count	24	24
					Sum	25.14	25.687
					Average	1.0475	1.070291667
					Variance	0.00647035	0.005156129


					ANOVA
					Source of Variation	SS	df	MS	F	P-value	F crit
					Sample	0.00225502	1	0.002255	0.383482	0.538939	4.061706	(This is the row variable or gender.)
					Columns	0.00623352	1	0.006234	1.060054	0.30883	4.061706	(This is the column variable or Degree.)
					Interaction	0.00641719	1	0.006417	1.091288	0.301892	4.061706
					Within	0.25873675	44	0.00588

					Total	0.27364248	47


	Interpretation:
For Ho: Average compas by gender are equal					Ha: Average compas by gender are not equal
					What is the p-value:
					Is P-value < 0.05?
					Do you reject or not reject the null hypothesis:
	If the null hypothesis was rejected, what is the effect size value (eta squared):
					Meaning of effect size measure:

For Ho: Average compas are equal for all degrees					Ha: Average compas are not equal for all grades
					What is the p-value:
					Is P-value < 0.05?
					Do you reject or not reject the null hypothesis:
	If the null hypothesis was rejected, what is the effect size value (eta squared):
					Meaning of effect size measure:

	For: Ho: Interaction is not significant			Ha: Interaction is significant
					What is the p-value:
					Is P-value < 0.05?
					Do you reject or not reject the null hypothesis:
	If the null hypothesis was rejected, what is the effect size value (eta squared):
					Meaning of effect size measure:

					What do these three decisions mean in terms of our equal pay question:


												Place data values in these columns
5.	Using the results up thru this week, what are your conclusions about gender equal pay for equal work at this point?													Dif

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