4. Next, please go to this URL: http://digitalfirst.bfwpub.com/stats_applet/stats_applet_1_anova.html

It says: The F statistic for one-way ANOVAand its P-valuedepend both on the group means (black dots in this applet) and the spread (standard deviation) and number (n) of observations within each group (colored dots). Let's vary each and see what happens.

A. Vary Difference between Group Means = Size of Treatment Effect

Move the group means (drag the black dots) so they are all about the same - what's your F-value? _______

Move the means so they are each about 1 point apart (such as approx. 6, 5, 4) what's your F-value? _______

Move the means so they are each about 2 points apart (such as approx. 8, 6, 4) what's your F-value? _______

4A. So, as the difference between means gets larger the F-value gets ________ and it is ______ likely to be significant.

B. Change Variability within the Group (SD or spread of individual scores)Click New sample - to get fresh random data. Record your initial values: F = ____ p = ______

Then move the Standard deviation slider both ways and notice what happens to the scores (dots), F and p-values.

With SD very low: F = ______ p = ______ With SD very high F = ______ p = ______

C. Effects of Sample Size. Click New Sample - to get fresh data. Initial n = 20 - Initial values: F = ____ p = ______

Move the sample size slider to n = 5, what is F = ____ p =_____? Move to n = 50, what is F = ____ p =_____?

4C. To summarize, ANOVA is likely to be significant when differences between group means are ______,

spread within the group is ______ and when sample size is _______ (use large or small for each blank).

PART 2: Using JASP to do a One-Way ANOVA problem.

Open the Excel .csv data file called Attachment Sleep. This dataset comes from a study on the effects of attachment style on sleep patterns of children. Specifically, the amount of time they spend in the deep sleep stage called delta waves. Read it into JASP. Add value labels to AttachmentGrp: 1= secure, 2= anxious, 3= avoidant. Save your work.

Test to see if the attachment styles differ in deep sleep. (ANOVA is always two-tailed -no more directional tests!)

5. What is the IV?: __________________________ the DV? ___________________________________

6. Write Hypotheses in words

Null H₀: ______________________________

Alt. H₁: ______________________________

NOTE: BEFORE RUNNING A HYPOTHESIS TEST - ALWAYS RUN DESCRIPTIVES, FREQ on Nominal DATA. Check the n's of the groups (10 in each?), look for missing values, data entry errors, outliers, non-normal data etc.

TO RUN the TEST - SELECT ANOVA - Classical, ANOVA

• Specify your DV (DeltaSleep).
• Specify your IV (AttachmentGrp) - move into Fixed Factors box
• Display - select Descriptive Stats, estimate of effect size

7. ANOVA Summary Table - copy your ANOVA summary table from JASP below.

8. Complete this Summary table - rounding results to 2 decimal places to be consistent with APA format.

SS df MS F p

Between (Attachment)

Residuals (within)

9. What do these ANOVA results mean? Is there is a significant difference in sleep between the 3 groups? ___

What is the F-value? ________ p-value _______ Is it significant? _____________

A significant F-value tells us there is a difference somewhere between the means. To find out which groups differ from each other we run Post-hoc tests to compare two groups at a time.

10. RUN POST HOC TESTS. Use the default test- Tukey test, select your IV (Attachment). Add Descriptives Plot- move Attachment to Horizontal Axis, select Display error bars.

Copy the Post-Hoc Comparisons Table below (and the graph if you want) from JASP results.

10a. Looking at the Post-hoc test table, which group(s) differ significantly from each other?

10b. Which groups do not differ significantly from each other?

11. Write your conclusion to this study in 2 APA style sentences below. Report the basic results on the significance of the hypothesis test first. Then report which groups differed from the post hoc tests and report the group means.