How to do the test:

- State your Null Hypothesis in the form:

"The dependent variable is not related to the independent variable in a linear fashion" - Choose a Critical Significance Level (α: alpha)

This is typically α = 0.05 - Calculate the test statistic

Use a spreadsheet to calculate your results,**or**

Access a helpsheet for SPSS

and check here for data entry into SPSS - Reject or accept your Null Hypothesis

**Either**compare the calculated statistic with Critical Value,

If F ≥ F_{critical}→ reject H_{0}→ significant result

If F < F_{critical}→ accept H_{0}→ non-significant result

**or**

Look at the calculated probability (*P*value)

If*P*≤ α → reject H_{0}→ significant result

If*P*> α → accept H_{0}→ non-significant result - Report your results

Plot your data using the appropriate graphs

(Regression test: F_{df regression, df error }= …,*P*= …) - If your regression test is significant, you can use your model for prediction , using a linear model of the form:

*y = bx + c*

(where*y*is the dependent variable ,

*x*is the independent variable ,

*b*is the slope of the line and

*c*is the constant or intercept )

Use the coefficient of determination, R^{2}, to indicate how much of the variability in*y*is explained by the regression

View an example report