Part 1 – Conducting a Repeated Measures ANOVA Manually You will use the following data to go step-by-step through a hypothesis test, by hand, for the DASS Stress subscale pre/post/follow-up data mimicked from the Rackoff et al. article (2022).  A sample of n = 585 college students were selected to participate in the study. In the sample, all students took a the DASS measure pre-intervention, post-intervention, and one month following intervention. The data necessary for you to complete this hypothesis test is provided in the table below. Pre-intervention Post-intervention Follow-up All Times n = 585 n = 585 n = 585 N = 1755 T = 16716 T = 13730 T = 13217 G = 43663 SS = 3703.015 SS = 7899.726 SS = 5543.173 ΣX2 = 1115653        = 1099779   Research Question: Is there a significant difference change in stress from pre-intervention to post-intervention to follow-up as measured by the DASS stress subscale? Step 1 à State your hypotheses State both your null and alternative hypotheses in the space below.

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Part 1 – Conducting a Repeated Measures ANOVA Manually

You will use the following data to go step-by-step through a hypothesis test, by hand, for the DASS Stress subscale pre/post/follow-up data mimicked from the Rackoff et al. article (2022).  A sample of n = 585 college students were selected to participate in the study. In the sample, all students took a the DASS measure pre-intervention, post-intervention, and one month following intervention. The data necessary for you to complete this hypothesis test is provided in the table below.

Pre-intervention

Post-intervention

Follow-up

All Times

n = 585

n = 585

n = 585

N = 1755

T = 16716

T = 13730

T = 13217

G = 43663

SS = 3703.015

SS = 7899.726

SS = 5543.173

ΣX2 = 1115653

 

 

 

 = 1099779

 

Research Question:

Is there a significant difference change in stress from pre-intervention to post-intervention to follow-up as measured by the DASS stress subscale?

Step 1 à State your hypotheses

State both your null and alternative hypotheses in the space below.

 

 

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