Correlation Coefficient SPSS

Introduction: The Correlation Coefficient(r) is a test of how strongly data sets are related to each other. The test is commonly used along with linear regression, which gives us the linear relationship between two variables. The coefficient then gives us the strength of that relationship. SPSS can work out the correlation coefficient formula almost instantly.

Step 1: Click “Analyze,” then click “Correlate,” then click “Bivariate.” The Bivariate Correlations window will appear.

Step 2: Click one of the variables in the left-hand window of the Bivariate Correlations pop-up window. Then click the center arrow to move the variable to the “Variables:” window. Repeat this for a second variable.

Step 3: Click the “Pearson” check box if it isn’t already checked. Then click either a “one-tailed” or “two-tailed” test radio button. If you aren’t sure if your test is one-tailed or two-tailed, see: Is it a one-tailed test or two-tailed test?

Step 4: Click “OK” and read the results. Each box in the output gives you a correlation between two variables.

One-Variable Chi-Square Tests with SPSS

Introduction: Before performing the one-variable chi-square test, coded values for the relevant variable should appear within a row of the SPSS Data Editor. In addition, the “values” cell of the Variable View screen should contain the coding frame. Including the coding frame instructs SPSS to display each category’s name, rather than numerical code, in output. With data organized this way, the researcher can perform the one-variable chi-square test with the following steps.

Step 1: Choose “non-parametric tests” from the Analyze pull-down menu.

Step 2: Choose “chi-square” from the options provided. A Chi-Square Test window should appear on the screen.

Step 3: Highlight the name of the relevant variable from the list appearing in the upper left corner of the window. Click on the arrow to the right of the list to move the name of the variable to the Test Variable List.

Step 4: Redefine expected values if necessary. SPSS assumes equal expected values. However, if expected values are unequal, define them within the Expected Values section of the window. To do so, choose “values” and then input the expected values or percents, clicking on the ADD button after each one.

Step 5: Click OK.

Multiple-Variable Chi-Square Tests with SPSS

Introduction: Multiple-variable chi-square tests address differences in frequencies of a cross tabulation, the data, entered in SPSS should appear as it does for the creation of a cross tabulation. Thus, coded data for each of the variables in a multiple-variable chi-square test must reside in a column of the SPSS Data Editor. As always, inputting the coding frame into the “values” cell of the Variable View screen allows for the output to display category names.

Step 1: From the Analyze menu, choose “descriptive statistics,” and then “crosstabs.” A Crosstabs window should appear on the screen.

Step 2: Assign variables to row, column, and layer positions in the same way described in Chapter 2. Highlight each variable individually and move it to the row, column, or layer position by clicking on the arrow to the left of the appropriate box.

Step 3: Click on the “statistics” button, located at the bottom of the Crosstabs window. A Crosstabs: Statistics window should appear.

Step 4: Select “chi-square” from the options in the Crosstabs: Statistics window and click “continue.” The basic Crosstabs window should, once again, appear.

Step 5: Click OK.

Linear Regression Analysis using SPSS Statistics

Introduction: Linear regression is the next step up after correlation. It is used when we want to predict the value of a variable based on the value of another variable. The variable we want to predict is called the dependent variable (or sometimes, the outcome variable). The variable we are using to predict the other variable's value is called the independent variable (or sometimes, the predictor variable).

Step 1: Choose analyze

Step 2: In the menu that appears, we go to regression

Step 3: A new menu appears. Choose linear

Step 4: A new dialogue box appears. 

Step 5: From the list of variables on the left, we will first choose our dependent variable, in this case ‘reading score’, and then click on the button next to dependent. The variable name now appears in the ‘dependent’ box. 

Step 6: Next, choose ‘math scores’ and click on the arrow next to the ‘independent’ box. Then we click on ‘ok’.