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JASP OUTPUT: MIXED ANOVA, there will be 2 ANOVA tables, Main effect for…

- - - - look at the within-subjects ANOVA table and IV1 * IV2
        
        is p significant?
        
        YES
        
        look at the descriptives table and the descriptives plot
        
        Approach 3: Bonferoni post-hoc
        
        what inferences can you make from the graph
        
        NO
        
        what is the p value
    - - IF it is significant, how many conditions did you have
        
        2 conditions
        
        first mention the main effect
        
        then mention the averages
        
        On average ................in [condition a] ....... more, (M = , SD = ) compared to [condition b] (M =, SD = )
        
        Complete write up
        A significant main effect of [state IV] (F ([df for IV],[df for residuals ]) = [state the F], [insert p value], ɲ² p = [state eta square]).
        On average ................in [condition a] ....... more, (M = , SD = ) compared to [condition b] (M =, SD = )
        
        A significant main effect of [state IV] (F ([df for IV],[df for residuals ]) = [state the F], [insert p value], ɲ² p = [state eta square]).
        
        3+ conditions
        
        we need to look at the descriptives and follow up test you did
        
        Post hoc (2 tailed)
        
        you need to look at the descriptives and the post-hoc
        
        it was found through the post-hoc test that there was/was not a significant IV1 IV2 interaction (p =?). Use the descriptive statistics table to describe the findings*
        
        should look like
        Participants in the 1 beer condition deviated more (M = 19.56, SD = 4.41) compared to participants who had no beer (M = 15.31, SD = 3.96)
        :black_flag: when collecting M and SD, look down that conditions column, not across (duh)
        
        2 more items...
        
        Planned contrast (1tailed)
        
        There was a significant main effect of [state IV1]
        (F ([df for IV],[df for residuals ]) = [state the F], [insert p value], ɲ² p = [state eta square])
        should look like
        (F (2,28) = 28.46, p <.001, ɲ² p = .72)
      - IF it is NOT significant
        
        I guess you can describe this? TBC :red_flag:
  - - - 2 conditions
        
        first mention the main effect
        
        then mention the averages
        
        On average ................in [condition a] ....... more, (M = , SD = ) compared to [condition b] (M =, SD = )
        
        Complete write up
        A significant main effect of [state IV] (F ([df for IV],[df for residuals ]) = [state the F], [insert p value], ɲ² p = [state eta square]).
        On average ................in [condition a] ....... more, (M = , SD = ) compared to [condition b] (M =, SD = )
        
        A significant main effect of [state IV] (F ([df for IV],[df for residuals ]) = [state the F], [insert p value], ɲ² p = [state eta square]).
      - 3+ conditions
        
        we need to look at the descriptives and follow up test you did
        
        Post hoc (2 tailed)
        
        you need to look at the descriptives and the post-hoc
        
        it was found through the post-hoc test that there was/was not a significant IV1 IV2 interaction (p =?). Use the descriptive statistics table to describe the findings*
        
        should look like
        Participants in the 1 beer condition deviated more (M = 19.56, SD = 4.41) compared to participants who had no beer (M = 15.31, SD = 3.96)
        :black_flag: when collecting M and SD, look down that conditions column, not across (duh)
        
        M = 2dp (19.563 --> 19.56)
        
        2 more items...
        
        you get the p value from the post hoc test under pbonf
        
        Planned contrast (1tailed)
        
        There was a significant main effect of [state IV1]
        (F ([df for IV],[df for residuals ]) = [state the F], [insert p value], ɲ² p = [state eta square])
        should look like
        (F (2,28) = 28.46, p <.001, ɲ² p = .72)
    - - report the results of the test (F and p value). this will show that it is not significant