Regression Models

To perform regression analysis in SPSS, you can use the following steps:

Linear Regression:

1. Open SPSS:

• Launch SPSS and open your dataset.

2. Select Analyze:

• Navigate to the “Analyze” menu at the top.

3. Choose Regression:

• Under “Analyze,” select “Regression” and then choose “Linear.”

4. Specify Variables:

• Move the dependent variable (the outcome variable) into the “Dependent” box.
• Move the independent variables (input features) into the “Independent(s)” box.

5. Options (Optional):

• You can click on the “Statistics” button to request additional statistics.
• Click on the “Plots” button to request diagnostic plots.
• Explore other options as needed.

6. Click OK:

• Once you’ve set up your variables and options, click “OK” to run the linear regression analysis.

7. Interpret Results:

• Examine the output for coefficients, significance levels, R-squared, and other relevant statistics.

Multiple Regression:

1. Follow Steps 1-3:

• Follow the steps mentioned for linear regression.

2. Specify Variables:

• Move multiple independent variables into the “Independent(s)” box.

3. Click OK:

• Proceed with the analysis by clicking “OK.”

4. Interpret Results:

• Review the output for coefficients, significance levels, R-squared, and other relevant statistics.

Polynomial Regression:

1. Follow Steps 1-3:

• Follow the initial steps for linear regression.

2. Choose Options:

• After selecting “Linear Regression,” click on the “Options” button.
• Check the box for “Polynomial” and specify the degree of the polynomial you want to fit.

3. Specify Variables:

• Move the dependent and independent variables as usual.

4. Click OK:

• Proceed with the analysis by clicking “OK.”

5. Interpret Results:

• Examine the output for coefficients and other relevant statistics.

Remember, interpretation of the results is crucial, and you should pay attention to the significance of coefficients, goodness-of-fit measures, and any diagnostic plots to assess the assumptions of the regression models.