Reporting a split plot ANOVA

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Reporting a split plot ANOVA

Transcript of Reporting a split plot ANOVA

Reporting a Split-Plot ANOVA in SPSS

Note –

Note – the reporting format shown in this learning module is for APA. For other formats, consult specific format guides.

Note – the reporting format shown in this learning module is for APA. For other formats, consult specific format guides. It is also recommended to consult the latest APA manual to compare what is described in this learning module with the most updated formats for APA.

A typical example of a split-plot analysis report might be:

A typical example of a split-plot analysis report might be: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

Let’s break this down:

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the F ratio for the 1st main effect. We compare

this value with the F critical.

If the F ratio is greater than the F critical then we

would reject the null hypothesis.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the degrees of freedom for gender

- 2 levels (female & male) - 1 = 1.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the degrees of freedom for error value.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the F ratio for the 2nd main effect

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the Mean Square for the Error Value

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the p value indicating that result was statistically

significant.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

F ratio or value for the 2nd main effect

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

Degrees of freedom for 4

levels of time (4-1 = 3)

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

Degrees of freedom for the error value.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the F ratio for the 2nd main effect

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the Mean Square for the Error Value

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the p value indicating that result of the 2nd main effect was

statistically significant.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

F ratio or value for the interaction effect

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

Degrees of freedom for (2-1=1)

levels of gender TIMES (4-1=3)

EQUALS 3 time X

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

Degrees of freedom for the error value.

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the F ratio for the interaction effect

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This is the Mean Square for the Error Value

Let’s break this down: “The main effect of Gender was significant, F(1, 19) = 7.91, MSE = 23.20, p < 0.01, as was the main effect of Time, F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The interaction of these two factors was not significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

This means that the result is not significant.