1. (4) Complete the missing numbers.

   Descriptive Statistics

   N

   Range

   Minimum

   Maximum

   Mean

   Std. Deviation

   Variance

   Skewness

   Kurtosis

   Statistic

   Statistic

   Statistic

   Statistic

   Statistic

   Std. Error

   Statistic

   Statistic

   Statistic

   Std. Error

   Statistic

   Std. Error

   Checkout line wait times were reasonable

   144

   1

   1

   10

   7.34

   2

   2.129

   3

   -.635

   .202

   -.361

   .401

   Valid N (listwise)

   144

   1 ) _____________________
   2 ) _____________________
   3 ) ___ __________________
   4 ) Does the distribution tail to the left or right. Explain________________________

2. ---

   (1 4 ) From the Secret Shopper Survey-
   Assume that prior studies show scores on employee knowledge = 7.2. Using the compare means process and a one sample t-test examine the results to see if there is a statistically significant difference. The results are displayed below- you do not have to run this file—but y ou need to set this up utilizing the FIVE step process we used in class. You will have to look up a critical value from the t-table and comp are it to the actual value, utilizing the 95% confidence level . Assume we do not have any prior reason to know whether these students will rate our employees ’ knowledge higher or lower.

   One-Sample Statistics
   	N	Mean	Std. Deviation	Std. Error Mean
   When asked a question the employee(s) was/were knowledgeable	153	7.80	1.775	.143

   One-Sample Test
   	Test Value = 7.2
   	t	df	Sig. (2-tailed)	Mean Difference	95% Confidence Interval of the Difference
   					Lower	Upper
   When asked a question the employee(s) was/were knowledgeable	4.164	152	.000	.597	.31	.88

   
   1) (10)Set up in the Five STEP Process (make sure you look up the critical t –value)
   2) (4) Comment on whether you have Practical significance based on calculating
   Cohen’s d . Show calculation and explain what it means in terms of practical sign ificance and its relative strength.
3. ( 10 ) CROSSTABS- from Secret Shoppers data
   A Crosstabulations & Chi-square comparison on question 10 having to do with "when checking out I received proper service" is displayed below.

   When checking out I received proper service * GENDER Crosstabulation
   Count
   		GENDER
   		MALE	FEMALE	Total
   When checking out I received proper service	VERY POOR SERVICE	2	0	2
   	MODERATELY POOR SERVICE	1	0	1
   	QUITE POOR	2	1	3
   	SERVICE SO SO	1	1	2
   	OKAY -NOT GREAT	2	5	7
   	OKAY-SLIGHLY POSITIVE	4	4	8
   	MODERATELY GOOD	9	6	15
   	QUITE GOOD	21	10	31
   	EXCELLENT	13	25	38
   	SUPERIOR	12	20	32
   	Total	67	72	139

   C hi-Square Tests
   	Value	df	Asymp. Sig. (2-sided)
   Pearson Chi-Square	14.751 a	9	.098
   Likelihood Ratio	16.117	9	.064
   Linear-by-Linear Association	4.205	1	.040
   N of Valid Cases	139
   12 cells (60.0%) have expected count less than 5. The minimum expected count is .48.

   Set up in the Five STEP Process (make sure you look up the appropriate Chi-square value)
4. (1 6 ) Below are data for car sales for 12 quarters. Interest rates, unemployment numbers , and car sales at Lincoln Land Auto are displayed.

   QTR	INTEREST RATES	UNEMPLOYMENT	CAR SALES
   1	5.6	8.2	300
   2	5.7	7.5	290
   3	7.8	6	250
   4	9.8	6.9	150
   5	4.5	5.9	290
   6	3.2	4.2	350
   7	4.5	5.6	250
   8	4.3	4.3	325
   9	6.7	6.5	245
   10	8.9	7.5	175
   11	4.6	7.8	400
   12	2.3	5.9	350

   
   Input this data into an SPSS file and then answer the questions as specified .
   1 a) (1) What would you r expectations be regarding the relationship between sales and interest rates ? Explain in 2-3 sentences.
   1b( (1) What about unemployment and sales ? Explain
   2) (1) Which of the three variables is the dependent variable? Explain.
   3a) (2) Create a scatter plot between sales and unemployment
   The following scatterplot is obtained
   3b) (2) Now do the same thing for sales and interest rates.
   4 ) (1) Looking at the two scatter plot s, what conclusion do you reach?
5. (1) Now run a correlation between the three variables(not including quarter)

6) (2) Which independent variable best explains sales ? Be very specific and justify you r answers with data!

7) Based on the best predicting independent variable, run a simple regression.

1. (2) Does the model fit at all ? - explain
2. (1) W hat per cent of variation does the independent variable explain?

c) (2) Write the regression equation. If you were told that the next quarter interest rates were going to be 7.2 % and unemployment was 6.8 % based on your SIMPLE regression model what would be your forecast of sales.

5. (10) Set up the following data set in SPSS and then answer the questions

An auto manufacturer is trying to improve braking times. Before new engineering was tried a pre-test on braking under various road conditions was conducted. After the changes, a post test was done under similar conditions. A lower score is better. Assume a 95% confidence level. Research is NOT undertaken unless it is assumed the new engineering will help will improve the situation.

1. (2) Would you assume a 1 tail or 2 tail test in this case? Explain
2. (1) Assuming 11 d.f. what is the critical t for a one tail test ?
3. (1) What would be your conclusion be regarding the effectiveness of the new engineering on the brak ing performance. Is it statistically s ignificant?
4. (3) Provide 3 pieces of evidence to substantiate your claim.

5) (3) Based on Cohen’s d is there a practical difference? Show calc ulation .

Question 6 . (1 1 )

A university professor wants to emphasize the value of studying in exam performance. The professor gather s data on the amount of time students spend in the library and their scores on a test.

The data is provided below

Set up the data in an SPSS file and then answer the questions

1) (1) What is the correlation between the exam score s and library time?

2)(2) Is it statistically significant ? - provide evidence.

Run a simple regression with the appropriate dependent and independent variables.

3) (2) Is there evidence that the mo del fits ? Explain with evidence.

4) (2) What percent of variation does the model explain between dependent and independent variables?

5) (2) Write the regression equation for this model.

6) (2) If library time is 70 minutes predict the point estimate of score of the student.

7. (3) Suppose you want to test the effects of age and education on income (the dependent variable). You want to simultaneous see whe ther each variable impacts income and if there is an interaction between these two independent variables. Based on your experimental design you are able to classify the levels of income into 4 categories and education into 4 categories . What statistical technique would you use and why ? Explain in 3-4 sentences.

8. (5) You are doing an ANOVA study looking at the relationship between performance on a calculus test and the number of math courses taken. Group 1 has 50 people who have taken one course, group 2 -50 who have taken two courses and group 3 -50 that that have taken three . But you get some puzzling results. Someone points out that you have no t controlled for the students prior GPA ’s. In other words , your group s don’t appear to be a random selection of low, middle, and high GPA’s. Assuming you have the information on GPA s but i t is not the primary interest in the study, what statistical procedure might you run next.

9. (1 2 ) We are trying to analyze whether average age at three retirement centers is equal o r different. We do a sample at each center.

The data is as follows:

Center 1 ( n 1 = 22): 60, 66, 65, 55, 62, 70, 51, 72, 58, 61, 71, 41, 70, 57, 55, 63, 64, 76, 74, 54, 58, 73

Center 2 ( n 2 = 18): 56, 65, 65, 63, 57, 47, 72, 56, 52, 75, 66, 62, 68, 75, 60, 73, 63, 64

Center 3 ( n 1 = 23): 67, 56, 65, 61, 63, 59, 42, 53, 63, 65, 60, 57, 62, 70, 73, 63, 55, 52, 58, 68, 70, 72, 45

1. (3) Calculate the means, std. deviations for each of the three groups .
2. (2) Run an ANOVA -

3) ( 2 ) W hat is the null hypoth esis and alternative hypothesis?

4) (3) What is your conclusion about the null. Provide two pieces specific of evidence to support your conclusion.

5) (2) W hat groups, if any are statistically different using Bonferroni. Cut and paste table and answer question

10. (4) Complete the following table: for TV TIME EXAMPLE (file has been modified )

1)____________________________

2)___________________________

3)__________________________

4)_____________________________

11. (14) Complete the following Tables for regression: Based on Convenience stores- modified

Complete tables

1)_____________________________

2)___ _ _________________________

3)___ _ ________________________

4)_____ _______________________

Now answer the following questions

5) (2) Does the model seem to fit reasonably well ? Explain with specific evidence.

6) (2) What percent of variation in sales does the model explain? The _____________

7 (3 ) Write the regression equation.

8 (3) If the traffic count is 54,000 what would be the point estimate of the store’s sales ? (show calculation)

Price: $39.94

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Deliverable: Word Document