1. The data spreadsheet has three tabs with data, one for each exercise.
2. When required, add answers to your output by inserting 'New Text' into your SPSS output. (EX: RA1.2.a: [type an answer]
3. You will 'Add Content' at the end of the assessment by attaching the following:
4. A single pdf file of your cleaned up and appropriately labeled output.
5. Add a heading to include [your last name] RA 1 (ex: Hinerman RA1).
6. Add a footer to include the page number.
7. Labels should include the name of the exercise (ex: RA1.1) in both the content index (left side) and the body of the output.
8. The file should be named: RA1_[your last name] (ex: RA1_Hinerman)
9. The single .spv file from your cleaned up output described above.
10. Your .sav files used to run your analysis.
11. All files should be named as follows: RA1.[exercise]_[your last name] (ex: RA1.1_Hinerman)

RA1.1:

A researcher wanted to compare two different types of therapy on children's self-esteem and anger management skills. The therapies investigated were nondirective play therapy (i.e., child directs the play) and directive play therapy (e.g., therapist leads the child through structured play activities). A total of 12 children were included in the study with 6 children (3 boys and 3 girls) receiving each type of therapy. After six weeks of therapy, the childrens' self-esteem (measured on a 10 to 50 scale) and anger management skills (measured on a 5 to 25 scale) were assessed. Open the file and perform the appropriate analyses in SPSS to answer the questions below.

• RA1.1a: Create value labels for therapy and gender. For therapy, 1 = "nondirective" and 2 = "directive." For gender, 1 = "male" and 2 = "female."
• RA1.1b: Run the Case Summaries procedure on the data.

RA1.2:

A researcher collected data on the reading performance and number of hours of television watched per day of 30 children. The gender and socioeconomic status (SES) of each participant were also collected. The data file contains the variables gender, ses, hourstv, and readingscores. For gender 1 = "male", and 2 = "female." For ses, 1 = "low," 2 = "middle," and 3 = "high." The reading scores are on a 0-50 scale with higher scores indicating better reading performance. Open the data file in SPSS and perform the appropriate analyses to answer the questions below.

• RA1.2a: Create value labels for gender and ses.
• RA1.2b: Report the frequencies for gender and ses.
• RA1.2c: Report the mean and standard deviation for hourstv and readingscores for the entire sample.
• RA1.2d: Report the mean and standard deviation for hourstv and readingscores separately for males and females.
• RA1.2d1: Which group has the highest mean on each variable?
• RA1.2d2: Which group has the largest standard deviation?
• RA1.2e: Report the mean and standard deviation for hourstv and readingscores for gender layered by ses.
• RA1.2e1: Which group watches the most television on average?
• RA1.2e2: Which group has the highest mean reading scores?

RA1.3:

Data were collected from 10 sophomores at a local university, including their gender (1 = "male," 2 = "female"), the number of hours they studied per day (hoursstudied), the number of cups of coffee they drank per day (cupscoffee), and their grade point average (gpa). Open the file and perform the appropriate analyses in SPSS to answer the questions below.

• RA1.3a: Crea a bar chart for gender and print your results.
• RA1.3a1: How many males and females are in the data set?
• RA1.3b: Cre a histogram for hoursstudied and print your results.
• RA1.3b1: What is the mean number of hours studied per day?
• RA1.3c: C a scatterplot using the variables gpa and hoursstudied (put gpa on the Y-axis).
• RA1.3d: C A boxplot of cupscoffee and print your results.
• RA1.3d1: Are there any outliers in the plot?
• https://docs.google.com/spreadsheets/d/1Gc0Hkul1YBPlrDMlg8fO3sjuvdaj6ips5_tfZs9aUWM/edit