1. A Simple Guide to Using SPSS ( Statistical Package for the Social Sciences) for Windows

2. 2 Introduction

3. 3 Steps for Analyzing Data Enter the data Select the procedure and options Select the variables Run the procedure Examine the output

4. 4 Getting Started with SPSS for Windows To Start an SPSS session: Or launch the software from Start menu Double-click on the short cut if you can see it

5. 5 Select Type in data and click OK to open an empty SPSS Data Editor window.

6. 6 Data Editor will open

7. 7 The Data Editor window consists of two pages, indicated by the page tabs at the bottom-left of the Editor window. The Data View is the ‘data page’ on which all the information will be entered.

8. 8 Define the Variable Names Click the Variable View tab at the bottom of the Data Editor window.

9. 9 The second page is the Variable View page on which we define the variables to be analyzed.

10. 10 Define the variables Name that are going to be used. In this case, 13 variables are needed: ID, gender,…………... Rules for naming variables –Must not contain spaces –Must begin with a letter or @ –Certain characters such as !, ?, and * are not allowed –Must not be one of the keywords such as AND, NOT, EQ, BY, or ALL –Must be unique. No other variable in a data file can have the same name. In SPSS version 12 or later, a variable name can have a maximum of 64 characters made up of letters and/or numbers. In earlier versions, only eight characters are permitted.

11. 11 Click the Data View tab to continue entering the data.

12. 12 The names you entered in the Variable View are now the headings for the first 13 columns of the Data View

13. 13 Define the Variable Click the Variable View tab at the bottom of the Data Editor window.

14. 14 Define the Variable - Type By default all Data are Numeric Change the Non-numeric Data by Click the button in the Type cell to open the Variable Type dialog box.

15. 15 Comma format uses commas as thousands’ separators. 1,234.56 Dot format uses a dot as thousands’ separator and a comma instead of a dot for the decimal point. 1.234,56 Scientific notation is useful for displaying very small or very large numbers. 1.23E+08 represents 123,000,000. 1.23E-08 represents. 0.0000000123 Dollar format will display data as money, i.e. the values are displayed with a $ sign in front. $1,234.56 Custom Currency format needs to be defined before use. In the two examples we have customised for pounds sterling and euros. £1,234.56 and €1,234.56 Date formats SPSS has a variety of date and time formats available. Variable Type

16. 16 Set the variable's type of ID, to String. Click OK to save your changes A string is a sequence of characters (letters, symbols, digits) which is treated as a label by the system, i.e. Values of a string variable are not numeric, and hence not used in calculations. A string variable is a qualitative variable

17. 17 Both Type and Measure will be changed

18. 18 Repeat Setting of the variable's type with Gender to String. Set the variable's type of Salary, to Dollar. Click OK to save your changes

19. 19 Define The maximum number of characters (digits or letters) appear in the data view window When you select String as variable Type, and in order to be viewed in the data view window, you have to increase the width to > 8 if you are intending to write more than 8 characters

20. 20 Display decimal points, even though their values are intended to be integers. To hide the decimal points in these variables type 0.

21. 21 Define the Variable – Labels Labels will be displayed in the output. Variable Label –Providing useful descriptive information of variables. than variable name. –Can be up to 255 character allows you to list a more extensive label for your variable. Eight character variable names are difficult to remember, and we recommend that you always exercise the option of listing a more descriptive label. Useful to include the unit of measurement in the label

22. 22 In the Label column of the ID row, type Employee code. Type Education level as the label for the ed-lev variable……..etc

23. 23

24. 24 Value Labels allows you to provide labels for the various levels of a variable. For example, value labels can be used to specify that M stands for Male and F stands for Female.

25. 25 To Define Variable label, Select the Values cell in the gender row and click the button to display the Value Labels dialog box.

26. 26 Type “f” for the Value and “female” for the Value Label. Click Add to have this label added to your data file. Repeat the process, but this time type “m” for the Value and “male” for the Value Label. Click OK to implement your changes.

27. 27

28. 28 Because string values are case sensitive, you should make sure you are consistent with your cases. A lower case “m” is not the same as a capital “M”.

29. 29 Repeat the process for education level

30. 30 Repeat the process for Smoking status

31. 31 Repeat the process for Physical activity

32. 32 Define the Missing Values In SPSS, there are no empty cells within the data file If you don't take steps to filter or identify this data, your analysis may not provide accurate results.

33. 33 For numeric data, blank data fields or those containing invalid entries are handled by converting those fields to system missing. The reason a value is missing may be –Failure to understand the question –Refused to answer –Data entry mistakes –Don’t know the answer –The question is not applicable to the respondent –answer in a format not expected

34. 34 We need to be careful to select a value for the missing value that is one that the variable cannot possibly take. Example if we were measuring the age of pre-school children, 3 would not be an appropriate choice for the missing value; 99 might be better because such a score could not actually represent a real case.

35. 35 Select the Missing cell in the Age row and click the button to open the Missing Values dialog box.

36. 36 In this dialog, you can specify up to three distinct missing values, or a range of values plus one additional discrete value. Select Discrete Missing Values. Type 0 as the missing value and leave the other two boxes blank. Click OK to implement your changes.

37. 37 Now that the missing data value has been added, a label can be applied to that value. Select the Values cell in the age row and click the button to open the Value Labels dialog box.

38. 38 Type 0 for the Value. Type No Response for the Value Label.

39. 39 Click Add to have this label added to your data file. Click OK to implement your changes.

40. 40

41. 41 Click the Missing Values cell for the sex variable. Click the button in this cell to open the Missing Values dialog box. Missing values for string variables Missing values for string variables are handled similarily to those for numeric values.

42. 42 Select Discrete Missing Values. Type NR for the missing value. Click OK to save your changes Missing values for string variables are case sensitive. So, a value of nr is not treated as a missing value.

43. 43 Now you can add a label for the missing value. Select the Values cell in the sex row and click the button to open the Value Labels dialog box.

44. 44 Type NR for the Value. Type No Response for the Value Label. Click Add to have this label added to your project. Click OK to implement your changes

45. 45 Define the Variable -Column Format Column Format is used to define column width for the variable in the Data View. If the defined and actual width of a value are wider than the column, asterisks (*) are displayed in the Data View.

46. 46 Used to define column alignment in the Data Editor window

47. 47 Used to Specifying the level of measurement for the variable.. SPSS defines variables as measured in one of three ways. Scale is for interval/ratio data.. Ordinal is for variables whose values represent categories with some inherent order between them, such as social class, attitudinal scales (e.g. agree, neutral, disagree). Nominal is for categorical variables with values which are not sequentially ordered, they are just names. By default, new numeric variables are set to Scale and variables with text (or string) values are set to Nominal.

48. 48

49. 49 Entering Data Directly

50. 50 Begin entering data in the first row, starting at the first column. Enter the value for each variable. Move the cursor or Press key or right arrow key to move to next variable.

51. 51 Leave blank or use user-defined missing value if no answer. Press key to move to next row.

52. 52 Each row represents a single case (observation) Each column is a single variable

53. 53 Change the View - Value Labels Data entered as numeric codes can be displayed as value labels. which can help to make your data more readable.

54. 54 From the menus choose: View Value Labels Or alternatively press this button Change the View - Value Labels

55. 55 Change the View - Value Labels The labels are now displayed in a listbox, which has the benefit of suggesting a valid response and providing a more descriptive answer.