1. 1 An Introduction to SPSS for Windows Jie Chen Ph.D. 6/4/20161

2. 2 ABSTRACT The goal of this hands-on workshop is to enable you to perform useful data analysis using IBM SPSS Statistics 19. The topics covered include: entering and reading data, documenting the file with variable and value labels. Examining frequency and crosstab tables for individual and group data. statistical hypothesis testing and graphic output. Participants will be provided with extensive notes on the topics covered in the workshop, work with sample datasets and will produce examples of the graphic output available from the program. 6/4/20162

3. 3 What is SPSS SPSS, short for Statistical Package for the Social Sciences, is a computer application designed to manage, analyze and graph data. With SPSS you can input raw data or retrieve a previously defined data file and compute a variety of statistics. 6/4/20163

4. 4 Topics Starting SPSS for windows – Data Editor, Output, and Chart Editor Windows Entering data into SPSS manually – Defining variable and value labels Reading data into SPSS – from an SPSS and Excel files Recoding variables Statistical procedures: Statistical graphs: 6/4/20164

5. Statistical procedures and graphs Statistical procedures – Frequency distribution – Cross tabulation and Chi-square test – Descriptive statistics – Independent sample t-test – One-way ANOVA Statistical graphs – Bar chart, error bar chart – Histogram 6/4/20165

6. 6 References SPSS Base 19.0 for Windows User’s Guide SPSS Base 19.0 Syntax Reference Guide SPSS Base 19.0 Applications Guide SPSS Professional Statistics 19.0 SPSS Advanced Statistics 19.0 Using SPSS for Windows (Green, S.B. et al.) 6/4/20166

7. 7 Starting SPSS for Windows Click on Or Start/Programs/IBM SPSS Statistics When SPSS first runs, the ‘Data Editor’ window opens. – Data View window used to input data – Variable View window used to define variables 6/4/20167

8. 8 SPSS Data Editor Window

9. 9 Entering and Reading Data into SPSS Entering raw data manually using the Data Editor Importing an SPSS data file Open an Excel data file 6/4/20169

10. 10 Entering Raw Data Using the Data Editor Suppose the following is a data set with 3 observations and 3 variables 84 8 1 65 16 1 56 13 1 To enter this data manually, do the following: 6/4/201610

11. Entering Raw Data 1. In the Data Editor window, click on the first cell (row 1, first column). 2. Type in the first row (observation) of data, pressing the Tab key after each number entered Type 84 (Tab) 8 (Tab) 1 (Tab) 3. Position the cursor over the cell in the first column (var00001) of the second data row. Type 65 (Tab) 16 (Tab) 1 (Tab) 4. Type the following data into third row 56 13 1 11 6/4/201611

12. 14 Data Editor Window with New Data

13. 15 Saving data as an SPSS system file 1. Click on File…Save As (make sure the SPSS Data Editor window is the active window). 2. A dialog box will appear. 3. Verify that the desired folder and extension name are chosen in the dialog box. 4. Type a file name in the File Name text box, for example ‘myfile’. 5. Click the Save button to save the data. 6/4/201613

14. 14 Exiting SPSS 1. Click File…Exit SPSS. 2. Click the No button in the Save Contents message boxes. 6/4/201614

15. Opening an SPSS Data file 1.Click File/Open/Data on the main menu 2.The “Open File” dialog box will appear 3.Click on the up one level tool in the dialog box until you reach the Desktop level Desktop /Workshop/SPSS 1.Double click on user folder 2.Click Sample1 in the files list box. 3.Click Open to open the SPSS data file 15 6/4/201615

16. 16 SPSS Data File Displayed in Data Editor Window

17. 17 Statistical Procedures in SPSS The Analyze menu contains a list of general statistical analysis categories. Most of the categories are followed by an arrow(>), which indicates that there are several statistical procedures available within the category; they will appear on a submenu when the category is selected. 6/4/201617

18. 18 Statistical Procedures: Tables and Charts For categorical variables: – Frequency distribution – Bar Charts For continuous variables – Descriptive statistics – Histogram 6/4/201618

19. 19 Getting a Frequency Table 1. Click Analyze on the main menu. 2. Click Descriptive Statistics… Frequencies from the Analyze menu. 3. The frequency dialog box will appear 4. Click the left-mouse button on the region variable in the dialog box 5. Click the right-arrow button to place the region variable on the Variable(s) list in the dialog box. 6. Click OK to run the frequency analysis 7. The SPSS output window will appear containing the result. 6/4/201619

20. 20 SPSS Output window

21. A Simple Bar Chart 1.Click on Graphs\Legacy Dialogs\Bar... 2.The Bar Charts dialog box appears. 1.By default, the Simple Bar Chart is selected. 2.Click Define, push button. 3.Put region into Category Axis Dialog text box Click Ok 24 6/4/201621

22. The output of a Simple Bar Chart 26

23. Chart Editor To put data label – Click on data label mode and to it put on a bar To change bar shape – Click on Editor/Properties – Depth & Angle To change bar color – Click on Properties – Fill & Border Copy or export a chart 6/4/201623

24. 3D Bar Chart with colors 6/4/201624

25. Cluster Bar Chart To have a bar chart to display a cross tabulation – From crosstabs – From Bar Chart manual 6/4/201625

26. 26 Building a Histogram Chart 1. Click Graphs… Histogram from main menu. 2. The Histogram dialog box appears. 3. Click fincome, then click the right-arrow button to place fincome into variable list of the dialog box. 4. Click Display Normal Curve check box to have SPSS display a normal curve superimposed over each histogram. 5. Click OK. 6. The SPSS output window appears with the histogram chart. 6/4/201626

27. 27 Histogram of Personal Total Income with Normal Curve

28. 28 Sample Data in Excel

29. 29 Reading data from an Excel File 1. Click File…Open. Alternatively, you can click the Open File button. 2. The “Open File” dialog box will appear 3. Click the drop-down arrow on the Files of Types: list, scroll to the Excel choice and click on it. 6/4/201629

30. 30 Summary Report of Spreadsheet File in Output Navigator Window.

31. 31 Spreadsheet Data in SPSS for Windows

32. 32 Adding Labels To allow longer variable and value description we may need – Variable Labels – Value Labels – Defining missing values To open Variable View window by clicking Variable View tab, on the left bottom corner. 6/4/201632

33. 33 Adding Variable labels Click Cell of (Race,Label) to type in the description for the Race variable, for example “Race of Respondent”. 6/4/201633

34. 34 Entering Value Labels cell (Race, Values) 1. Click on the cell (Race, Values) 2. Click on the square shade 3. The Window of Define Labels: race is open 4. Click in Value text box, Type 1 4. Click in Value Label text box, Type White 5. Click Add push-button to add label to the list box. 6/4/201634

35. 35 6. Click in Value text box and type 2. 7. Click in Value Label text box and Type black So on. 8. Click Continue push-button to process the value label. 6/4/201635

36. 36 Define missing value cell (Race, Missing) 1. Click on the cell (Race, Missing) 2. Click on the square shade 3. The Window of Define Missing Values: race is open 3. Click in Discrete missing values text box, type 9. 4. Click Continue push-button to process. the defining missing value. 6/4/201636

37. 37 Frequency table with missing value defined

38. 38 Viewing Value Labels Click Data View tab to go back to Data Editor Window Click race variable Click View… Value Labels. Alternatively, click the label tool on the tool bar. 6/4/201638

39. 39 Recoding Values into a New Variable 1. Click Go to Data icon to return to Data Editor window. 2. Click Transform…Recode…Into Difference Variables from the main menu. 3. The “Recode” dialog box will appear to choose variables to recode and name the new variables. 6/4/201639

40. 40 Opening a Recode Dialog Box

41. 41 4. Place age in the Input Variable->Output Variable box by double-clicking on that variable. 5. Click in the Output Variable Name text box and type Group to create the new variable. 6.Click in the Label text box and supply a variable label. Then click on Change button to register the new variable. 6/4/201641

42. 42 6. Click on Old and New Values… 7. Click second Range radio button type 35. Then click in the Value box under New Value and type 1, click on Add. 8. Do the equivalent for the group from 36 to highest, assigning value of 2. 9 Click on Continue, then on OK in the main Recode dialog box. 6/4/201642

43. 43 Opening a Frequency Procedure

44. 44 Frequencies Output for GROUP

45. 45 Adding Value Labels for the New Variable Group 1. Double-click on Group in the Data Editor window. 2. Click Labels push-button. 3. Type 1 in Value text box and youth in Value Label text box then click Add push-button. 6/4/201645

46. 46 4. Type 2 in Value text box and maturity in Value Label text box then click Add push- button. 5. Click Continue push-button to process the value labels. 6. Click OK push-button to store the labels. 7. Click the Display Value Labels tool button to check Value Labels. 6/4/201646

47. 47 More Statistical Procedures Using a large data file with 1,000 observations for the following statistical procedures: Independent - Samples T-test One-Way ANOVA Crosstabulation Chi-Square Tests 6/4/201647

48. 48 Compare Means for Two Groups 1.Click Analyze/Compare Means/ Independent Sample T-test… 2.The T-test dialog box will appear; – Place ptotinc in the Test Variable(s) list and – place group in the Grouping Variable. – Click Define Groups. The Define Group dialog box will appear. Type 1 in Group 1 text box and 2 in Group 2 text box. 3. Click Continue, then Click OK. 48

49. 49 The output of T-test for Comparing Means of PTOTINC in Two Groups

50. 6/4/201650 Displaying Mean Differences Click Graphs/Error Bar Chose Simple and click Define push button Put ptotinc into Variable dialog box Put sex into category axis dialog box Click OK to obtain the display

51. 6/4/201651 Error Bar Chart of Income By Gender

52. 6/4/201652 One-Way ANOVA Use Explore procedure to produce summaries of the groups involved in the analysis; Perform a one factor analysis; Request multiple comparisons to see specifically which population groups differ; Plot the results using an error bar chart;

53. 6/4/201653 Exploring the data Click Analyze/Summarize/Explore Put ptotionc in Dependent List: box Put race in Factor List: box An exploratory analysis of personal total income will be presented for each race ethnicity group.

54. 6/4/201654 Running One-Way ANOVA Click Analyze/Compare Means/One-Way ANOVA Choose ptotinc as the Dependent variable Choose race as the factor variable Click OK

55. 6/4/201655 The Dialog Box of ANOVA

56. 6/4/201656 The Multiple Comparisons Click Dialog Recall Tool In the One-Way ANOVA: dialog box click Post Hoc… Then the One-Way ANOVA: Post Hoc Multiple Comparisons dialog box will be opened. Check LSD, Bonferroni, Tukey and Duncan

57. 6/4/201657 The Multiple Comparisons

58. 6/4/201658 Graphing the Results To display the sample group means along with their 95% confidence bands Open the Error Bar Dialog Box by clicking Graphs/Error Bar/Simple Specify the dependent (ptotinc) and independent (race) variables Click Ok

59. 59 A Simple Crosstabulation 1.Click on Analyze…Descriptive Statistics… Crosstabs… from the main menu. 2. The Crosstabulation dialog box will appear 3. Click on Region and place it in the Row(s) list and Click on Group and place it in the Column(s) list. 4. Click on OK to process the request. 5. The output window with Crosstable will appear. 6/4/201659

60. 60 Addition Options 5. Click on Expected in Counts box, then click on Continue. 6. Click on Statistics button. The Crosstabs: Statistics dialog box appears. 7. Click on the Chi-square check box to select that test. 8. Click on Continue, then on OK. 6/4/201660

61. 6/4/201661 The Expected and Observed Counts Observed, checked by default, is the frequency where meet both raw and column condition Expected is the expected values of count can be evaluated for each cell. The Chi-square test is evaluated based on the difference of observed and expected values.

62. 6/4/201662 The Percentages Row percentages are computed within each row so that the percentages cross a row sum to 100 % Column percentages are computed within each column so that the percentages down a column sum to 100 % Total percentages sum to 100% across all cells.

63. 6/4/201663 A Cross Tabulation Table

64. 6/4/201664 A Cross Tabulation Table with Expected Counts

65. 6/4/201665 Chi-square test result

66. 6/4/201666 Association Measures Click Dialog Recall Tool Click Reset in the Crosstabs dialog box Put edu as the row variable and income as the column variable Click Statistics push button – Check Chi-square – Check Correlations – Check Gamma in the Ordinal options box Click Continue and then Click OK

67. 6/4/201667 Graphing Cross Tabulation Results Click Bar on the Graphs menu Chose Clustered and click Define Put income into Category Axis dialog box Put sex into Define Cluster dialog box Click % of cases push button to indicate the bar heights are to be based on percentages of the variables involved Click OK to graph the percentages for gender and income

68. 6/4/201668 Clustered Bar Chart Dialog Box

69. 6/4/201669 Bar Chart of Income by Gender

70. 6/4/201670 More Examples for Chi-square test To test the association between gender and personal income: Use sex as the row variable Use income as the column variable Check chi-square test statistic with p-value