Psychology week one assignment

RSM801 Week 1 Assignment

In a survey with adult women, 150 participants answered questions about depression and media use.

Before we can explore relationships between these variables, we must check the data set for errors, outliers, and in the case of scales, transform and sum variables.

To begin, open the data file (CESD(1).sav, click on SAVE AS, once downloaded, open the file with SPSS)

Once the data is open in SPSS, notice the tabs at the bottom, there is a variable view and a data view.

· The data view allows you to see all the data (this is where you would enter new data).

· The variable view allows you to see the variables (this is where you would create new variables).

DESCRIPTIVE STATISTICS

We need to explore our data to get a beginning picture of what is happening.

First try ‘Descriptives’

· In the menu bar, click on ANALYZE/DESCRIPTIVE STATISTICS/DESCRIPTIVES

· a dialog box will open

· Highlight the variables:

Age

HHSize

· Click on the arrow in the middle that moves them to the box on the right

· Click on OPTIONS (click on any options that you might want to add)

· Click on RUN

· Your output file will now open

Q1) Provide the means for the following variables:

Age ____________

HHSize _________

Q2) Next, in the menu bar, click on ANALYZE/DESCRIPTIVE STATISTICS/FREQUENCIES

· Now highlight the variables:

Maritalstatus

Education

Work

· Click on the arrow in the middle that moves them to the box on the right

· Click on OPTIONS (click on any options that you might want to add)

· Click on RUN

· Your output file will now open

What percentage of the sample is:

Married _______________

Has less education than a college degree? (Hint: Look at cumulative frequencies)

________________

Worked for pay? _________________

Q3) For this assignment, you also need to generate a depression score for each participant. There are 20 items from the CES-D scale (variables CES_0001 to CES_0020).

Transform->Recode into Different Variables

To start, you will need to reverse score the four positive items (4, 8, 12, and 16).

1. Transform->Recode into Different Variables

2. Click on “Display Variable Names” so that you can see the variable names

3. Click on CES_0004 and move it to the middle.

4. The 'Output Variable' will be Named CES4rev with the 'Label' Reverse score of CES4 Categories. 

5. Repeat steps 3 and 4 for CES_0008, CES_0012, and CES_0016 (with the output variables being called the corresponding name – e.g., CES8rev, CES12rev, and CES16rev).

6. Click on 'Old and New Values

7. Code those individuals who reported “Most or all of the time” ('Old Value' = 3 into 'New Value' = 0)

8. Code those individuals who reported “Occasionally or moderate amount of time” ('Old Value’ = 2 into 'New Value = 1)

9. Code those who reported “some or a little of the time” ( 'Old Value = 1 into 'New Value = 2)

10. Code those who reported “rarely or none of the time” ( 'Old Value = 0 into 'New Value = 3)

11. Click OK

12. Run Analyze->Descriptive Statistics->Frequencies comparing the reversed and original frequencies for items 4, 8, 12 and 16

13. Include the output here for Q4 frequencies (copy and paste frequencies for CES_0004 and CES4rev). Does this match what you would expect to find?

Q4) Transform->Compute Variable

There are times when we will want to compute a new variable based on the data we have. Create a new variable summing the 20 items from the CES-D scale.

1. Click on Transform->Compute Variable

2. Your new variable ('Target Variable') will be called CESDTOT.

3. Use the following formula to generate the new variable: (CES_0001 + CES_0002 + CES_0003 + CES4REV + CES_005 + CES_006 + CES_007 + CES8REV + CES_009 + CES_010 + CES_011 + CES12REV + CES_0013 + CES_0014 + CES_0015 + CES16REV + CES_0017 + CES_0018 + CES_0019 + CES_0020)

4. This formula takes the 20 items (including the 4 that needed to be reversed) and sums them together.

Use the 'Explore' command in SPSS (Analyze->Descriptive Statistics->Explore) and determine the measures of central tendency and spread for CESDTOT (Depression sum score) and Media use (Media use Score).

· A dialog box will open.

· You will need to put your variables of interest into the DEPENDENT LIST box (similar to how you did it in DESCRIPTIVES previously).

· For your dissertation, you may also want to include a grouping variable into the FACTOR LIST box (A factor is the same thing as an independent variable; Thus, this allows us to break the statistics up by group membership). For now we will leave this box empty

· Click on RUN

· Review the new output

· Summarize the mean and SD for CESDTOT and Media Use (round numbers to two decimal points)

Q5) Some of the data is missing for individual CES-D items. The important thing in dealing with missing data is to figure out if the data is missing randomly or if there is some pattern (reason) to why the data points are missing. Does there appear to be a pattern to the missing data?

How might one deal with the missing data? (Do not do this, simply report what you think based on our discussion this week).

Q6) Examine the Descriptive Statistics output you generated for CESDTOT and MediaUse for outliers. Remember that univariate outliers are those with very large standardized scores (z scores greater than 3.3) and that are disconnected from the distribution. SPSS DESCRIPTIVES will give you the z scores for every case if you select save standardized values as variables and SPSS FREQUENCIES will give you histograms (use SPLIT FILE/ Compare Groups under DATA for grouped data).

Did you find any univariate outliers? Briefly write up your conclusion about univariate outliers, using data to back up your report.

Q7) Finally, write up the results of your descriptive statistics analysis (Q1-6) in APA format as if you were describing the analysis for your dissertation (it will probably be only a paragraph). Make sure to include figures (e.g., a box plot).  The APA formatting may be difficult, but it will be helpful in the long run to spend some time learning it properly now.  

If you have any questions, do not hesitate to ask! This is meant to be a learning exercise.