## How to do the test:

1. State your Null Hypothesis in the form:
"The dependent variable is not related to the independent variable in a linear fashion"
2. Choose a Critical Significance Level (α: alpha):
This is typically α = 0.05.
3. 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.
4. Reject or accept your Null Hypothesis.
Either
1. Compare the calculated statistic with critical values (Critical values table):
• If F ≥ Fcritical → reject H0 → significant result.
• If F < Fcritical → accept H0 → non-significant result.
2. Look at the calculated probability (P value):
• If P ≤ α → reject H0 → significant result.
• If P > α → accept H0 → non-significant result.
5. Report your results:
Plot your data using the appropriate graphs.
(Regression test: Fdf regression, df error = …, P = …)
6. 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, R2, to indicate how much of the variability in y is explained by the regression.