SPSS Bivariate Statistics

Transcription

1 SPSS Bivariate Statistics Social Science Research Lab American University, Washington, D.C. Web. Tel. x Course Objectives In this tutorial you will learn to: Measure relationships between two variables using these processes o Chi-Square o Gamma o Lambda o Pearson s r Measure if a relationship between two variables is statistically significant using a T-test Note: This tutorial uses the World95.sav dataset. This is available on our website. Crosstabulation To run crosstabulations, go to Analyze > Descriptive Statistics > Crosstabs. Select the variables for which you want the crosstabs. To specify more options, click on the Statistics and/or Cells button. Then click Continue and OK. The results will be displayed in the Output Editor. Let s do this for the age and college variables (see below graphic). 1

2 Chi-Square Test Suppose we want to know if there is a relationship between average female life expectancy and literacy. The appropriate test for this is the Chi-square test which can be obtained through the Crosstabs dialog boxes. Click on the Statistic button and check Chi-square box. Select the variables average female life expectancy and people who read (%) *Literacy+. Then click Continue and OK. SPSS will produce some output which looks like this: 2

3 Chi-square is a useful technique because you can use it to see if there s a relationship between two ordinal variables, two nominal variables, or between an ordinal and a nominal variable. You look at the assymp. Sig column and if it is less than.05, the relationship between the two variables is statistically significant. Lambda Statistic The Lambda statistic can only be used when both variables are measured nominally. To try Lambda out, go to the Crosstabs window. Click on Statistics and select Lambda. Select two nominal variables from the world95 dataset. The output below uses the variables Predominant climate and Religion numerically coded SPSS s Lambda Output Gamma Statistic The Gamma statistic on the other hand is used when both variables are measured ordinally. SPSS reminds you of this by placing them in separate boxes. To try Gamma out, go to the Crosstabs window. Click on Statistics and select Gamma. Select two nominal variables from the world95 dataset. The output below uses the variables GDP Per capita categories and Literacy Ordinal Variable SPSS s Gamma Output 3

4 Correlations In order to understand the basic relationship between Interval (Scale) variables you need to go to another window. To run correlations, go to Analyze > Correlate. Then select Bivariate, if you are interested only in the relationships between two variables, or Partial, if you are measuring the association between two variables but want to factor out the effect of other variables. Select the variables for which you want the correlation. Then click OK. Let s do both for the correlation between average female life expectancy and aids cases. The Bivariate Correlations Window SPSS s Bivariate Correlations Output 4

5 The table on the previous page shows you the correlation between two variables, one at a time. Pearson s r ranges between -1 and 1 and the further away it is from 0, the stronger the relationship between the two variables. SPSS also uses stars to show the strength of the relationship. Statistically significant relationships (unlike the one above) are marked with two stars. Hypothesis Testing T-test There are three types of t-tests: One-Sample T test to compare a single sample with a population value, Independent-Samples T test to compare two groups scores on the same variable, and Paired-Sample T test to compare the means of two variables within a single group. Analyze > Compare Means > Independent-Samples T Test. Select average female life expectancy as the test variable and predominant climate as the grouping variable. Click on the define groups button. Enter 1 (for dessert) as group 1 and 8 (for temperate) as group 2. Click continue then OK. SPSS Independent-Samples T-test output Go to Analyze > Compare means > Paired-sample T-test. Pick average female life expectancy and average male life expectancy for variable 1 and 2. Put the variables in the box by clicking the arrow. Click OK 5

6 SPSS s Paired-sample T-test output 6