Spssexam sav

Advanced Multivariate Statistics

Take-Home Exam I

Instructions:

· You have been assigned datasets with your initials (for example: ABCPart1.sav where ABC are your initials).

· Locate the datasets with your initials on the Moodle website for this course.

· Use your assigned dataset to answer the exam questions, as follows:

· The dataset ABCPart1.sav should be used to answer questions in Part 1.

· The dataset ABCPart2.sav should be used to answer questions in Part 2.

· The dataset ABCPart2.sav should be used to answer questions in Part 3. (You will be using the same data for Parts 2 &3.)

· The dataset ABCPart4.sav should be used to answer questions in Part 4.

· Assume an alpha level of .05.

· Create a Word document for your answers to each part of the exam. Label the Word document with your initials (ABC_Part1.docx, ABC_Part2.docx, etc.), where ABC are your initials.

· Save the SPSS Output and Syntax file from each part of the exam with your initials (e.g., ABCPart1.spo, ABCPart1.spv, etc.).

· If needed, you may copy and paste relevant pieces from the output into the Word document that contains your answers to the exam questions.

· Email your four Word documents, four SPSS Syntax files, and four SPSS Output files as attachments. There should be twelve attachments in total.

· Your Exam is DUE Tuesday

PART 1

Use the ABCPart1.sav dataset you have been assigned to answer the questions in Part 1.

A. Conduct the appropriate analyses to predict the life expectancy of males.

1) What are the research questions and hypotheses you will test? (10 pts)

2) Check the data for outliers, and decide which, if any, you will omit. Describe your actions and rationale. Include SPSS output as backup. (10 pts)

3) Describe any concerns you observe about normality, skewness, kurtosis. Even if you find issues with normality, skewness, and/or kurtosis, make no transformations. (10 pts)

4) Determine which type of analysis is most appropriate. Describe your decision process. (10 pts)

5) Conduct the analyses. (30 pts)

6) Describe the analyses and your findings as if you were writing it up for publication in an APA, peer-reviewed journal. Be sure to include relevant tables and figures. (30 pts)

7) If the United Nations asked for your advice on one thing they could do to improve the life expectancy of females, what one thing would you suggest they change, based on the data? (10 pts)

Variables in the ABCPart1.sav dataset include:

· pop2012 Population in 2012

· urban Urbanization % of pop in urban areas

· lifeexpm Life expectancy of males

· lifeexpf Life expectancy of females

· region Region

· develop Level of development

· docs Doctors per 100k (ln)

· radio Radios per 100k (ln)

· phone Phones per 100k (ln)

· gdp Gross Domestic Product (GDP) per capita (ln)

· hospbeds Hospital beds per 100k (ln)

· continent Continent

PART 2

Use the ABCPart2.sav dataset you have been assigned to answer the questions in Part 2.

B. Conduct the appropriate analyses to examine differences in bonuses paid to employees based on region, gender, and the combination of both.

1) What are the research questions and hypotheses you will test? (10 pts)

2) Check the data for outliers, and decide which, if any, you will omit. Describe your actions and rationale. Include SPSS output as backup. (10 pts)

3) Determine which type of analysis is most appropriate. Test all relevant assumptions; if your findings altered your analytical plan, describe. (10 pts)

4) Conduct the analyses, including any post hoc comparisons. (40 pts)

5) Describe the analyses and your findings in words as if you were writing it up for publication in an APA, peer-reviewed journal. Be sure to include relevant tables and figures in APA format. (30 pts)

Variables in the ABCPart2.sav dataset include:

· Bonus2014: Bonus received in 2014 in US dollars

· Tenure: Length of time in the organization

· Sick Days: The total number of sick day occurrences in the past year

· Tardiness: The total number of tardy occurrences in the past year

· Hourly Wage: Current hourly wage in US dollars

· Status: Current employment status

· Performance Score: Supervisory ratings on most recent annual performance review

· Survey Ratings: Employee responses to survey questions (1=Strongly Disagree; 2=Somewhat Disagree, 3=Neither Agree Nor Disagree, 4=Somewhat Agree, 5=Strongly Agree)

· Overall satisfaction with the job

· Satisfaction with benefits

· Satisfaction with training opportunities

· Career advancement

· Satisfaction with support from supervisor

· Perceived fairness in how decisions are made

· Commitment to the company

Data Coding Sheet for the ABCPart2.sav dataset (what the values for each variable represent)

Gender

1) Male

2) Female

Race

1) White

2) Black

3) Native American

4) Asian / Indian subcontinent

5) Pacific Islander

Status

0) Voluntary

1) Employed

9) Involuntary

Region

1) Northwest

2) Southwest

3) Northeast

4) Midwest

5) Mid-Atlantic

6) Southeast

Performance Score

1) Poor

2) Fair

3) Good

4) Very Good

5) Excellent

Supervisor Code

1) Smith

2) Perkins

3) Adler

4) Harper

5) Santos

6) Blackstone

7) Carson

8) Goldberg

9) Handler

10) Gonzales

11) Warner

12) Stephens

13) Brown

14) Bowers

15) Zeigler

16) Otembwe

17) Livingston

18) Green

PART 3

Re-use the ABCPart2.sav dataset you have been assigned to answer the questions in Part 3. Note this is the same dataset as used in Part 2.

C. Add a covariate of your choice to the analyses conducted in Question B.

1) What are the research questions and hypotheses you will test? (10 pts)

2) Check the data for outliers, and decide which, if any, you will omit. Describe your actions and rationale. Include SPSS output as backup. (10 pts)

3) Determine which type of analysis is most appropriate. Test all relevant assumptions; if your findings altered your analytical plan, describe. (5 pts)

4) Conduct the analyses, including any post hoc comparisons. (40 pts)

5) Describe the analyses and your findings in words as if you were writing it up for publication in an APA, peer-reviewed journal. Be sure to include relevant tables and figures in APA format. (25 pts)

PART 4

Use the ABCPart4.sav dataset you have been assigned to answer the questions in Part 4.

D. Conduct the appropriate analyses to examine differences in speed to complete a race under different footwear conditions (barefoot, basic sole, cushioned sole) and surfaces (sand or grass). All athletes were tested under all conditions.

1) What are the research questions and hypotheses you will test? (10 pts)

2) Check the data for outliers, and decide which, if any, you will omit. Describe your actions and rationale. Include SPSS output as backup. (10 pts)

3) Determine which type of analysis is most appropriate. Test all relevant assumptions; if your findings altered your analytical plan, describe. (10 pts)

4) Conduct the analyses, including any post hoc comparisons. (40 pts)

5) Describe the analyses and your findings in words as if you were writing it up for publication in an APA, peer-reviewed journal. Be sure to include relevant tables and figures in APA format. (30 pts)

Variables in the ABCPart4.sav dataset include:

· Gender

· BF_Sand Speed (in seconds), while Barefoot on Sand

· BF_Grass Speed (in seconds), while Barefoot on Grass

· BS_Sand Speed (in seconds), wearing a Basic Sole on Sand

· BS_Grass Speed (in seconds), wearing a Basic Sole on Grass

· CS_Sand Speed (in seconds), wearing a Cushioned Sole on Sand

· CS_Grass Speed (in seconds), wearing a Cushioned Sole on Grass