1. Analyzing Data

2. Learning Objectives You will learn to: – Import from excel – Add, move, recode, label, and compute variables – Perform descriptive analyses – Conduct simple correlations – Test reliability of measures – Conduct t-tests – Use syntax

3. https://catalyst.uw.edu/workspace/wjen/23868 /150329 Open Excel file: CurlyStraightStudy.xls

4. Create Meaningful Variable Labels Simple – Easily read by SPSS/PASW Distinct – Meaningful to you, and easy to distinguish from other variables.

5. Find and Replace in Excel Convert “String” Variables into Numeric Variables. Replace “999” or other missing data codes with blanks.

6. Show a classmate your completed Excel file

7. Download Excel file: computer science data.xls

8. Open SPSS/PASW by going to Start > All Programs

9. User Interface

10. Importing from Excel* Open an existing data source by clicking “Okay” (or click cancel and go to File > Open) Navigate to Excel file (file must be closed) - use drop down to select “.xls” files Select “toSPSS” worksheet with one click and then select “OK”

11. Main Window

12. Three windows in SPSS/PASW* 1.Main window – what you see now Data View – rows of data, like excel; one subject per row Variable View - where you see and edit information about your variables; one variable per row 2.Output window – after you run an analysis 3.Syntax – recording analyses

13. Output Window Output gets added to the file - can select and delete unnecessary output Save your output

14. Syntax Window Allows you to save your code for future use In SPSS dialog boxes, click “Paste” instead of “OK” Select and hit Ctrl-R to run syntax Use “*” to comment out – end comments with a “.”

15. Prepping Data in SPSS/PASW

16. Descriptive Statistics* Describe the characteristics of individual variables – Frequencies for categorical* variables Analyze > Descriptive Statistics > Frequencies – Means and standard deviation for continuous* variables Analyze > Descriptive Statistics > Descriptives How would you find out how many males and females you have? *Other names you might have heard: Continuous = Interval; Categorical = Discrete

17. Descriptive Statistics* Describe the characteristics of individual variables – Split by group Data > Split File> Compare Groups – Compare means and standard deviation for continuous* variables by Condition, Gender, etc. How would you find out the average age of each gender and the average overall age? *Other names you might have heard: Continuous = Interval; Categorical = Discrete

18. Recoding Variables* To group participants together based on their answers, you need to recode their answers Transform > Recode > Into Different Variables Highlight “year” move it into the box Type “year_r” in Name > Change

19. Recoding Variables* Click on Old and New Values In Old Value, type Freshman In New Value, type 1 Click Add Repeat for Sophomore (1), Junior (2), Senior (2)

20. Recoding Variables In Data View, scroll over to the right and you will see your new variable How would you label the values so you know what 1 and 2 means?

21. Labeling variable names In Variable view: g o to the Label column and type more descriptive name

22. Labeling variable values* In Variable view: label gender values with “male” and “female” – Click on grey box in Values column – Enter 1 for Value and Male for Label; repeat for 2 = Female In Data View: View > Value Labels

23. Computations in SPSS/PASW

24. Correlation A Pearson correlation computes relationships between continuous variables

25. Analyze > Correlate > Bivariate Can enter several variables to get a matrix of relationships Correlation*

26. if the p-value (“Sig.”) is less than.05, then the relationship between the two are significant There is a positive correlation between number of programming classes and reported likelihood of majoring in computer science, r(5) =.96, p <.05.

27. Assessing reliability* To figure out if two+ dvs “hang together”, select Analyze > Scale > Reliability Analysis In Items, enter the variables you would like to collapse across Click Statistics and check the Scale if Item Deleted box

28. Computing new variables* To do computation involving one or more variables, select Transform > Compute In Target Variable, type new variable name (weightedgpa) In Numeric Expression, type computation (MEAN(curentgpa, majorgpa)

29. Analyzing Data in SPSS/PASW

30. T-test* A t-test compares the means of two groups to each other Analyze > Compare Means > Independent samples t-test Which gender reports being more likely to major in computer science?

31. T-test* Click on Define Groups and put M and F in Groups 1 and 2

32. T-test* Women and men report being equally likely to major in computer science, t(3) = -1.63, ns.

33. What test you should use* Are your data continuous? If yes Do you have two groups to compare to each other? If yes Are your groups independent (between) or dependent (within)? If independent Independent samples t-test! If dependent Paired samples t-test!

34. * What kind of DV? Continuous What kind of IV(s)? Continuous# of IVs?OneCorrelationTwo +RegressionCategorical# of IVs?OneLevels of IV?Two Within-subjects or between-subjects? Paired samples t-test Independent samples t-test Three + One-way ANOVA Two + Within-subjects or between subjects? ANOVA (GLM Univariate) ANOVA (GLM Repeated Measures) Categorical What kind of IV(s)? Continuous Logistic regression Categorical Chi squared test What Test to Use

35. One way ANOVA (one IV but 3 levels ) Analyze  compare means  One-way ANOVA Next screen: – Dependent List: (your DV) – Factor: (your IV) Post hoc  Tukey (where groups differed) Options  Descriptives Looks at whether you have a statistically significant different between groups

36. Using SPSS syntax Allows you to save your code for future use In SPSS dialog boxes, click “Paste” instead of “OK” Select and hit Ctrl-R to run syntax Use “*” to comment out – end comments with a “.”

37. Selecting subjects* Data > Select Cases > Click “If…”

38. Selecting subjects* In box, type the criteria you want (gender = “M”) Use Boolean logic (&, |, ~=, ANY()) String variables needs quotes around their values To select everyone, go back to Data > Select Cases and select “All Cases”

39. Congratulations! You have learned how to – Import data into SPSS/PASW – Label variables and their values – Recode and compute new variables – Obtain frequencies and other descriptive statistics – Run a correlation – Test for reliability – Run a t-test – Run a 2x2 ANOVA – Use syntax

40. Project HW this Week (due Sunday 5pm) Should finish collecting you own project data by end of this week

41. Project HW this Week (due Sunday 5pm) Excel data template with 20+ subjects entered, ready for SPSS import – Logsheet entered separately – Freeze panes – No text in numeric fields – Variables named appropriately

42. This Wednesday Finish SPSS analysis and output – Group activity Time to work on Lab HW