Help with Linear Regression SPSS
Once you have completed the correlation of your data, you can use linear regression to predict one variable’s value based on another variable’s value. While linear regression SPSS methods aren’t something you can simply jump right in to, if you have the assistance of an expert, it’s not that difficult. With help, you’ll be able to use the independent or predictor variable to determine the value of the dependent or outcome variable. Linear regression has many different uses and can be used in a number of fields. You could even use it on your own SPSS report writing to determine if your grade (the dependent variable) can be predicted by how much time you spend studying (the predictor variable).
How to Do Linear Regression
If you’re not certain how to do linear regression in SPSS, the following steps will walk you through this process. Before you can do this, of course, you will have to have gathered your data first. There are some assumptions you’ll need to make on your data. You may discover that your information does not meet all of these assumptions. That’s actually fairly common when you are using data you’ve collected from the real world. Don’t worry about that. There are often ways to overcome this issue.
- Your variables are ratio or interval variables that were measured at continuous levels.
- The variables have a linear relationship.
- You have no data points that are significantly different from the rest of the data. These anomalies are called significant outliers and are vertically distance from your regression line.
- Your data passes a Durbin-Watson statistic, which means that it has the independence of observations.
- The data displays homoscedasticity, which means it is contained within a set of straight lines with no significant amount of space near any of the lines. If your data points can be enclosed in an oval or half circle, the information is likely heteroscedastic rather than homoscedastic.
- Any errors or residuals are normally distributed.
Next, you can use SPSS to perform linear regression using the following steps. Don’t worry if you haven’t checked your data to make certain it meets these assumptions. You’ll actually be able to do that in SPSS as you’re preparing for linear regression.
- Click on Analyze, Regression, Linear. The Linear Regression box will open.
- You should see a list of your variables in the box on the left. Click on the variable that will be the dependent one, then click the arrow to move it to the Dependent box. Do the same with the independent variable.
- You can click on the Statistics button and on the Plots button to check that your data passes assumptions 3, 4, 5, and 6. If it does, continue.
- Click on the OK button to generate your linear regression results. You will receive a number of different tables, some of which you may not need.
Tips for Doing Linear Regression in SPSS
If you’re working on linear regression in SPSS, these tips may help:
- If you’re getting an invalid result, it may be because your data isn’t passing the six assumptions. Double-check to make certain that it does.
- If you have more than one independent variable, you will need to do a multiple regression rather than a linear regression.
- You can use a Kolmogorov-Smirnov test to determine if your data has multivariate normality.
- When creating a graph of a simple regression, you’ll create a scatter graph. The dependent variable will be shown on the vertical or Y axis, while the independent variable will be on the horizontal or X axis.
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