SPSS I

            Course Instructor Guide

 

Outline:

 

  1. Introduction to SPSS
  2. Data Entry
  3. Frequency Distributions and Descriptive Statistics
  4. Output
  5. Edit a Chart
  6. One Sample t-Test
  7. Independent Sample T-Test
  8. Correlation
  9. The Process
  10. Next week
  11. Open class for Q&A

 

 

 

In Detail:

 

  1. Introduction to SPSS
    1. Web site

                                                               i.      http://www.spss.com

    1. SPSS

                                                               i.      Statistical Package for the Social Sciences

    1. Designed to be a relatively comprehensive data analysis package for use in research and business
    2. Since this is a complex program dealing with statistics it is best if you have a statistics background and understanding of

                                                               i.      Basic Terms

1.      Case

2.      Variables

a.       Nominal

b.      Ordinal

c.       Interval

d.      Ratio

3.      Values

4.      Normal Distribution

5.      Standard deviation

6.      Analysis

a.       One-Sample T-Test

b.      One-Way ANOVA

c.       Correlation

7.      It is expected that you have a grasp of these

    1. Since it is expected that you know statistics this course is designed to teach statisticians how to use this SPSS application

                                                               i.      There is not enough time to cover both statistics and the program

    1. Please limit questions to how to use SPSS, not to statistics and quantitative analysis
  1. Data Entry
    1. Open SPSS

                                                               i.      If a window appears asking, What would you like to do?

1.      Select

a.       Type in Data

b.      OK

                                                             ii.      Toolbars

1.      Cover toolbars

    1. Data editor

                                                               i.      You are currently in the SPSS Data Editor

                                                             ii.      Spreadsheet-type layout

1.      Columns and rows

2.      Headings

3.      Row numbers (no value to these numbers)

4.      Use arrow keys to move from cell to cell

                                                            iii.      Type in data and name variables (two ways to type in)

1.      After typing in a number hit enter

a.       1-3, then, 1,1,1, then 87-92

1

1

87

2

1

53

3

1

92

 

 

2.      Type a number then hit tab to complete the row

4

1

70

5

1

78

 

 

                                                           iv.      Coding

1.      SPSS is a quantitative analysis program

a.       Works with numbers

b.      We try to convert text to code

                                                                                                                                       i.      Gender

1.      F = 1

2.      M = 2

                                                             v.      Show how to delete

1.      Rows

2.      Columns

3.      Data

    1. Variable View

                                                               i.      Choose bottom left tab, Variable View

                                                             ii.      Name

1.      Variable names can only be between 1-8 characters

2.      Any combination of numbers and letters, but must begin with a letter

3.      Name variables as:  student, gender, and score

                                                            iii.      Decimals

1.      Change all to 0

                                                           iv.      Label

1.      More description of the field

2.      score

a.       Midterm Score

                                                             v.      Values

1.      Code Information

a.       Click the button to the right of the text box

                                                                                                                                       i.      Value, 1

                                                                                                                                     ii.      Value Label, Female

                                                                                                                                    iii.      Value, 2

                                                                                                                                   iv.      Value Label, Male

                                                           vi.      Go back to Data View

  1. Frequency Distributions and Descriptive Statistics
    1. Example

                                                               i.      15 men and 15 women in an introductory psychology class have taken their midterms

                                                             ii.      In this example, we wish to construct frequency distributions and obtain some basic descriptive statistics for the variables gender and score

    1. Complete the following

Student

Gender

Score

1

1

87

2

1

53

3

1

92

4

1

70

5

1

78

6

1

73

7

1

91

8

1

60

9

1

77

10

1

82

11

1

85

12

1

33

13

1

88

14

1

98

15

1

88

16

2

89

17

2

73

18

2

91

19

2

76

20

2

75

21

2

89

22

2

81

23

2

83

24

2

68

25

2

86

26

2

55

27

2

89

28

2

89

29

2

70

30

2

93

    1. Data Analysis

                                                               i.      On the menu toolbar choose Analyze > Descriptive Statistics > Frequencies

1.      Move the variables from the left to the right box

2.      After choosing which variables to use always check what options or preferences are available before choosing OK

a.       Move gender and score

b.      Check the Display Frequency Tables box

c.       Choose Statistics

                                                                                                                                       i.      Check all boxes for dispersion, central tendency, and distribution

                                                                                                                                     ii.      Click continue

d.      Choose Charts

                                                                                                                                       i.      Choose Histogram, with Normal Curve

                                                                                                                                     ii.      Choose Continue, and OK

e.       Choose Format

                                                                                                                                       i.      Leave alone

f.        Click Continue, and OK

  1. Output
    1. Show how there are now two files open

                                                               i.      The data file is the .sav file

                                                             ii.      The output file is the .spo file

    1. Save the data file as midterms.sav on the desktop
    2. Save the output file as midterms.spo on the desktop

                                                               i.      Look on the desktop at the two files

    1. Go back to the output file

                                                               i.      Discuss the right and left window views

                                                             ii.      Briefly discuss

1.      Each table

2.      Both Histograms

  1. Edit a Chart
    1. Right click on the Score Histogram

                                                               i.      Choose SPSS Chart Object > Open

1.      Now in a third window

a.       Run through the following

                                                                                                                                       i.      The chart options button

                                                                                                                                     ii.      The line style button

                                                                                                                                    iii.      Label style

                                                                                                                                   iv.      The text button

                                                                                                                                     v.      Select the columns (chart series), and use the color button

2.      Close the window

a.       The change takes place in the output file

    1. Close the output file
  1. One Sample t-Test
    1. In the Data Editor Choose File > Open > Data

                                                               i.      In the SPSS I folder choose iqexample.sav

    1. Example

                                                               i.      The principal of the Lake Merced elementary school believes that the students in his school are more intelligent, on the average, than the general population of students in the United States.  The mean IQ of the general population is 105.  So we have conducted a study where we picked out random students at the Lake Merced elementary school.  The results are in the iqexample file.

                                                             ii.      In this problem we are testing the null hypothesis that the mean IQ of all school children in the United States equals 105.  Is the mean of this sample significantly different from 105?

    1. Analysis

                                                               i.      Choose Analyze > Compare means > One-Sample T Test

1.      Move IQ to the box labeled Test Variables

                                                             ii.      Then, click the box labeled Test Value

1.      Enter 105

                                                            iii.      Check Options

1.      Confidence Interval 95%

2.      Exclude cases analysis by analysis

                                                           iv.      Click OK

                                                             v.      In the output file, examine the results

1.      Is a mean difference of 5.73 large enough to be significantly different 105?  The results of the t-test show that t=3.900, with 29 (N-1) degrees of freedom.  The two-tailed p-value for this result is .001.  The result is considered statistically significant if the p-value is less than the chosen alpha level usually .05 (and .01), so the result is considered statistically significant and the null hypothesis is rejected

    1. Close the output file
  1. Independent Sample T-Test
    1. Open independentsamplettest.sav
    2. Example

                                                               i.      The SFSU psychology department conducted a study to determine the effectiveness of an integrated / experimental methods course as opposed to the traditional method of taking the two courses separately.  It was hypothesized that combining the two would be better.  To determine whether there actually was a difference in student performance as a result of integrated versus separate training; the final research projects of 20 students from an integrated course and 20 students from the traditional course were evaluated.  There scores are listed in this file.

                                                             ii.      In this problem we are testing the null hypothesis that there is no difference in student performance as a result of the integrated versus traditional courses, that is, that the mean difference between the conditions in the population from which the sample was drawn is zero.

    1. Analysis

                                                               i.      Choose Analyze > Compare Means > Independent-Samples T Test

1.      Move the dependent variable (score) to the right

2.      Move the independent variable (cond) to the right (grouping variable)

a.       The ?? means you need to Define Groups

                                                                                                                                       i.      Cond group 1, and group 2

                                                                                                                                     ii.      Type in 1, and then 2

3.      Check Options

4.      Click continue, and then OK

5.      Output File

a.       Discuss tables

                                                                                                                                       i.      Levene’s Test for Equality of Variances represents a test of the hypothesis that the populations from which the groups were sampled have equal variances.

                                                                                                                                     ii.      The most commonly used test is the row labeled Equal variances assumed.  Because we are assuming that the two population variances are equal, a pooled variance estimate is used to combine the two sample variances to obtain the most accurate estimate of the variance common to both populations

                                                                                                                                    iii.      The observed t-value for this problem is 2.043, with degrees of freedom equal to 38.  The two-tailed probability of .048 is less than .05 and, therefore, the test is considered significant (thought barely) at the .05 level.

                                                                                                                                   iv.      The null hypothesis is rejected at the .05 level of significance

  1. Correlation
    1. Open correlations.sav
    2. Example

                                                               i.      Next, Mr. Van Damme believes that regular aerobic exercise is related to greater mental activity, stress reduction, high self-esteem, and greater overall life satisfaction.

                                                             ii.      In this example each subject filled out a series of questionnaires.  The results are as follows in this file.

                                                            iii.      In this problem, we are interested in calculating the Pearson product-moment correlation between each pair of variables.  In addition, for each pair we wish to test the null hypothesis that the correlation between the variables in the population from which the sample was drawn equals zero.

    1. Analysis

                                                               i.      Choose Analyze > Correlate > Bivariate

1.      Move all variables over to the right, except subject

2.      Select

a.       Pearson

b.      Two-tailed

c.       Flag Significant Correlations

3.      Choose Options

a.       Check Means and Standard Deviations

b.      Click Continue

4.      Click OK

b.      Output

                                                               i.      Examine tables

1.      Discuss the similar data information

  1. The Process

c.       Entering data and coding

d.      Changing variable information

e.       Running an analysis

                                                               i.      Choose the analysis

                                                             ii.      Choose variables to analyze

                                                            iii.      Set options

                                                           iv.      Run analysis

  1.  Next week

f.        Recoding into different variables, cross tabulations, regression, One-Way ANOVA

  1. Open class for Q&A