**Assignment 1**

**DUE**: Jan 24th before the start of class.

**LATE PENALTIES:** A late penalty of 10% per day late (including weekends and holidays) will apply to written assignments.

**DESCRIPTION**

Assignment 1 requires the student to generate a small data set using XLSTAT, convert the data to .sav format, and, in SPSS, conduct simple hypothesis tests.

The instructions are as follows:

1) Open Excel, then XLSTAT. Generate 21 columns of data. Column 1 should be 20 1's and 20 2's, in order. Columns 2 through 21 should be generated using the XLSTAT "preparing data" and "distribution sampling" functions. The first 20 rows of columns 2-21 should be generated randomly from a Normal distribution with mean of 10 and SD of 5. Specify "number of samples" = 20 and "sample size" = 20. The second 20 rows should be generated in the same way but rather than using a mean of 10, use a mean of 11. You should now have 40 rows and 21 columns looking something like this (2 points):

2) Open this data in SPSS and create an .sav file.

3) State the appropriate null hypothesis for tests of group 1 against group 2. (1 point)

4) In SPSS conduct t-tests of the difference between groups for each of the 20 columns of data. List all 20 p-values. (2 points)

5) For an alpha of .05 two-tailed, indicate the tests that lead to a rejection of the null. In how many cases was the p-value less than .05? (1 point)

6) For the same alpha, indicate the tests that did not lead to a rejection of the null. In how many cases was the p-value not less than .05? (1 point)

7) How many wrong decisions did you make? Explain (3 points).

**Grading**: The assignment is worth 10% of your course grade. There are 7 questions, the percentage assigned to each question is given above.

**SUBMITTING YOUR ASSIGNMENT**

Submit ONE MS Word file converted to a pdf containing your analyses, results and written work. To demonstrate that you have done your analyses correctly, take screen shot images of your Excel data file, your .sav data file and the results of your fist t-test. Include all images and written work in the MS Word file. For each question above then, you should have either an image or written work.

Name the file "ass_1_first name_second name.pdf". My file name would be: "ass_1_jeremy_jackson.pdf".

Submit your assignment on Blackboard under the "Assignments" tab in the main menu.

**Assignment 2**

**DUE**: Feb 23rd before the start of class.

**LATE PENALTIES:** A late penalty of 10% per day late (including weekends and holidays) will apply to written assignments.

**DESCRIPTION**

Assignment 2 is an analysis of the data contained in the file: assignment_2_data.xls

The data file contains 10 columns and 51 rows. Column names are in row 1 of the data file. The description of the columns follows:

1) Age: Age in years.

2) Hours studying: Hours per day student reports studying.

3) Hours sleeping: Hours per day student reports sleeping.

4) Hours commuting: Hours per day student reports traveling to or from work or school.

5) Hours working: Hours per day student reports working.

6) Hours per day in class: Hours per day student reports being in class.

7) Hours media: Hours per day student reports watching media on tv and/or computer.

8) Hours video games: Hours per day student reports playing video games.

8) Guns: Number of guns owned by student.

9) GPA: Student's reported cumulative GPA.

10) Trump: Student rating of Trump on a 1-7 scale with 7 being strongly support and 1 being strongly against.

**Analysis**: Use XLSTAT to perform the following 10 analyses:

1) What is the average age and standard deviation of age in years of the 50 subjects?

2) Transform age in years to a standard score using the mean and SD calculated above (do not use the XLSTAT function for this). Include a column of transformed scores in your data file. Call the column: "standardized age".

3) Calculate the mean and SD of the standardized scores to confirm that the mean is 0 and SD is 1.

4) Sort the file by age and then recode age into 3 categories: young, middle and old. Use 0-19 as young, 20-24 as middle and 25 or older as old. Use the codes of 1, 2 and 3 for the age categories. Report the percent young, middle and old.

5) Calculate the Pearson r between age in years and rating of Trump. Calculate the Pearson r between standardized age and rating of Trump. Calculate the Pearson r between the recoded age and rating of Trump.

6) Add up all of the "hours per day" variables (2 - 8). Include a column in your data file next to the standardized age column with the summed score. Call the column "Total hours"

7) Identify the cases with totals more than 24 hours. Include a column in your data file called "logical outlier". Code a "0" for a non-outlier and "1" for an outlier. How many logical outliers are there in the file?

8) Use the XLSTAT standardize function to standardize all 10 variables in your data file. Include 10 columns for the standardized variables. Call them Zage, Zhours studying, etc.

9) Generate a Pearson correlation matrix of the pairwise correlations between all 10 UNSTANDARDIZED variables in the file. Generate a Pearson correlation matrix of the pairwise correlations between all 10 STANDARDIZED variables in the file. Comment on the differences/similarities between the standardized and unstandardized matrices.

10) What kind of students like Trump?

**Grading**: The assignment is worth 10% of your course grade. There are 10 questions, each question is worth 1%.

**SUBMITTING YOUR ASSIGNMENT**

Submit ONE Excel file containing your analyses and results. Include all output/results on a second sheet. Name the sheet "results". Include all transformed, recoded and computed variables as described above on sheet 1 (the sheet the original data is in). On the "results" sheet you should have entries for questions: 1, 3, 4, 5, 7, 9 and 10.

Name the file "ass_2_first name_second name.xls". My file name would be: "ass_2_jeremy_jackson_xls".

Submit your assignment on Blackboard under the "Assignments" tab in the main menu.

**Assignment 3**

**DUE**: Mar 9th before the start of class.

**LATE PENALTIES:** A late penalty of 10% per day late (including weekends and holidays) will apply to written assignments.

**DESCRIPTION**

Assignment 3 is an analysis of the data contained in the file: assignment_3_data.xls

The data file contains 10 columns and 51 rows. Column names are in row 1 of the data file. The description of the columns follows:

1) Age: Age in years.

2) Hours studying: Hours per day student reports studying.

3) Hours sleeping: Hours per day student reports sleeping.

4) Hours commuting: Hours per day student reports traveling to or from work or school.

5) Hours working: Hours per day student reports working.

6) Hours in class: Hours per day student reports being in class.

7) Hours media: Hours per day student reports watching media on tv and/or computer.

8) Hours video games: Hours per day student reports playing video games.

8) Guns: Number of guns owned by student.

9) GPA: Student's reported cumulative GPA.

10) Trump: Student rating of Trump on a 1-7 scale with 7 being strongly support and 1 being strongly against.

**Analysis**: Use XLSTAT to perform the following 7 analyses:

1) Add a subject number to your data file. Note: DO NOT SORT or ALTER the file in any way before you do this. Include a column called "subnum" that contains the subject number. Make this the first column in your data file. (1 point)

2) Conduct a PCA of variables 2-8. Use the method shown in class to do this. Retain the "factor" scores for the first two components and insert them in to two columns. Name the columns, PC 1 and PC 2. (2 points)

3) What percentage of the total variance is accounted for by the first two factors? (1 point)

4) Conduct a linear factor analysis of variables 2-8. Use "Principal Factor Analysis". Retain the factor scores for the first two factors and insert them in to two columns. Name the columns, Factor 1 and Factor 2. (2 points).

5) Conduct the factor analysis again but now rotate the factors using Varimax rotation. Do not use "Kaiser Normalization". Retain the rotated factor scores for the first two factors and insert them in to two columns. Name the columns, Rotated Factor 1 and Rotated Factor 2. (1 point).

6) Produce a Pearson correlation matrix of all 10 manifest variables in the data AND the six latent variables you have saved. This will give you a 16x16 correlation matrix. (1 point)

7) Discuss the correlations between the latent variables and the manifest variables. (2 points)

**Grading**: The assignment is worth 10% of your course grade. There are 7 questions, the percentage assigned to each question is given above.

**SUBMITTING YOUR ASSIGNMENT**

Submit ONE Excel file containing your analyses and results. Include all output/results on a second sheet. Name the sheet "results". Include all transformed, recoded and computed variables as described above on sheet 1 (the sheet the original data is in). On the "results" sheet you should have entries for questions: 3, 6 and 7.

Name the file "ass_3_first name_second name.xls". My file name would be: "ass_3_jeremy_jackson_xls".

Submit your assignment on Blackboard under the "Assignments" tab in the main menu.

NOTE: Retain your data file, you will use it in assignment 4.

**Assignment 4**

**DUE**: Mar 16th before the start of class.

**LATE PENALTIES:** A late penalty of 10% per day late (including weekends and holidays) will apply to written assignments.

**DESCRIPTION**

Assignment 4 is an analysis of the data you produced in assignment 3.

**Analysis**: Use SPSS to perform the following 5 analyses:

1) Recode age into a new variable with 3 categories (young medium and old). Do exactly what you did in "step 4" of assignment 1. Now recode "hours studying" in to two categories (low and high). Use .5 hours per day or less as low and 1.5 hours a day or more as high. Ignore those students studying 1 hour per day. (1 point)

2) Conduct an ANOVA with age and hours studying as the IV's and "TRUMP" AS THE DV. (2 points)

3) Interpret the results of the ANOVA? Make sure to include a line graph of the cell means to aid in your interpretation. (3 points)

4) What do the results tell us about Trump supporters? (2 points).

5) Discuss the statistical and methodological veracity of recoding age and hours of study and using them as IV's in an ANOVA. (2 points).

**Grading**: The assignment is worth 10% of your course grade. There are 5 questions, the percentage assigned to each question is given above.

**SUBMITTING YOUR ASSIGNMENT**

Submit ONE Excel file containing your analyses and results. Include all output/results on a second sheet. Name the sheet "results". Include all transformed, recoded and computed variables as described above on sheet 1 (the sheet the original data is in). On the "results" sheet you should have entries for questions: 3, 4 and 5.

Name the file "ass_4_first name_second name.xls". My file name would be: "ass_4_jeremy_jackson_xls".

Submit your assignment on Blackboard under the "Assignments" tab in the main menu.