: Analyze > Regression > Linear .
Click Variable View to define your first variable (e.g., "Age" as numeric, scale). Then return to Data View to enter data manually or prepare for import.
Define (usually Numeric), Label (a descriptive name), and Measure (Nominal, Ordinal, or Scale). 2. Importing and Cleaning Data ibm+spss+statistics+27+step+by+step+pdf+work
Where you define the metadata for your variables, such as name, type, label, and measurement level.
by George and Mallery is the most popular resource for beginners. What it covers : Analyze > Regression > Linear
) value ranges from -1 to +1. A positive value indicates a positive relationship, while a negative value indicates an inverse relationship. Check the value to see if the correlation is statistically significant. 5. Exporting Your Work to PDF and Reports
Reading the Output: Look at . If the Sig. value is greater than 0.05, read the "Equal variances assumed" row. Look at the Sig. (2-tailed) value to determine statistical significance ( Workflow C: Pearson Correlation Define (usually Numeric), Label (a descriptive name), and
Drag your variables from the variables list onto the highlighted axis boxes. Click to render the visualization in your Output window. 4. Testing for Normality
Move your continuous dependent variable into the box.
To inspect your data for anomalies (like an age entered as "215" instead of "21"): Go to > Descriptive Statistics > Frequencies .