QUESTION IMAGE
Question
based on the results of your statistical analyses, select the correct values that correspond to the term in the first column.
f for the anova test
( df ) for the main effect of group (between - groups)
( df ) for error (within - groups)
p for the anova test
p for the difference between unrealistic doll and realistic doll groups
p for the difference between unrealistic doll and control (no doll) groups
p for the difference between realistic doll and control (no doll) groups
( eta^2 )
the values to choose from are 87, 0.979, 0.00, 0.875, 2, 303.306, with radio buttons for each term.
To solve this, we analyze each term in ANOVA:
1. \( F \) for ANOVA test
In ANOVA, \( F \) - statistic is a ratio of between - group variance to within - group variance. The value \( 303.306 \) is a typical magnitude for an \( F \) - statistic (large \( F \) can indicate significant differences). So \( F \) for ANOVA test: \( 303.306 \).
2. \( df \) for main effect (between - groups)
For a one - way ANOVA with \( k \) groups, \( df_{between}=k - 1 \). If there are 3 groups (unrealistic, realistic, control), \( k = 3 \), so \( df_{between}=3 - 1=2 \). Thus, \( df \) for main effect (between - groups): \( 2 \).
3. \( df \) for error (within - groups)
If total \( N \) (total number of observations) and \( df_{total}=df_{between}+df_{within} \), and if we assume \( N = 89 \) (since \( df_{within}=N - k \), and with \( k = 3 \), \( df_{within}=87 \) when \( N=90 \)? Wait, more simply, in typical ANOVA outputs, \( df_{within} \) is often a larger number. Here, \( 87 \) is a common \( df_{within} \) (e.g., if \( N = 90 \), \( df_{within}=90 - 3 = 87 \)). So \( df \) for error (within - groups): \( 87 \).
4. \( p \) for ANOVA test
The \( p \) - value for ANOVA (overall test) is often a small value (indicating significance). Here, \( 0.00 \) (or near - zero) is the \( p \) - value for the ANOVA test. So \( p \) for ANOVA test: \( 0.00 \).
5. \( p \) for unrealistic vs realistic doll groups
Post - hoc tests (like Tukey) for group differences: a non - significant \( p \) - value (close to 1) might be here. \( 0.979 \) is a large \( p \) - value (non - significant), so \( p \) for unrealistic vs realistic: \( 0.979 \).
6. \( p \) for unrealistic vs control groups
Another post - hoc test: \( 0.875 \) is a large \( p \) - value (non - significant), so \( p \) for unrealistic vs control: \( 0.875 \).
7. \( p \) for realistic vs control groups
Assuming similar non - significance, but if we follow the pattern, but since we have to match, but let's confirm: Wait, maybe I mixed, but the key is to match each term:
- \( F \) for ANOVA: \( 303.306 \)
- \( df \) between: \( 2 \)
- \( df \) within: \( 87 \)
- \( p \) ANOVA: \( 0.00 \)
- \( p \) unrealistic - realistic: \( 0.979 \)
- \( p \) unrealistic - control: \( 0.875 \)
- \( p \) realistic - control: (if we assume, but maybe another value, but from the given, we assign as above)
- \( \eta^{2} \): (not given in the options? Wait, the options are 87, 0.979, 0.00, 0.875, 2, 303.306. Maybe \( \eta^{2} \) is not in the options, but for the given terms:
Let's summarize the correct matches:
| Term | Correct Value |
|---|---|
| \( df \) for the main effect of group (between - groups) | \( 2 \) |
| \( df \) for error (within - groups) | \( 87 \) |
| \( p \) for the ANOVA test | \( 0.00 \) |
| \( p \) for the difference between unrealistic doll and realistic doll groups | \( 0.979 \) |
| \( p \) for the difference between unrealistic doll and control (no doll) groups | \( 0.875 \) |
| \( p \) for the difference between realistic doll and control (no doll) groups | (If we assume, but since the options are given, maybe the remaining value, but likely, the above are the key matches.) |
For example, if we were to mark each:
- \( F \) for ANOVA: circle \( 303.306 \)
- \( df \) between: circle \( 2 \)
- \( df \) within: circle \( 87 \)
- \( p \) ANOVA: circle \( 0.00 \)
- \( p \) unrealistic - realistic: circle \( 0.979 \)
- \( p \) unrealistic - control: circle \( 0.875 \)
(Note: The last two \( p \) - values for realistic - co…
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To solve this, we analyze each term in ANOVA:
1. \( F \) for ANOVA test
In ANOVA, \( F \) - statistic is a ratio of between - group variance to within - group variance. The value \( 303.306 \) is a typical magnitude for an \( F \) - statistic (large \( F \) can indicate significant differences). So \( F \) for ANOVA test: \( 303.306 \).
2. \( df \) for main effect (between - groups)
For a one - way ANOVA with \( k \) groups, \( df_{between}=k - 1 \). If there are 3 groups (unrealistic, realistic, control), \( k = 3 \), so \( df_{between}=3 - 1=2 \). Thus, \( df \) for main effect (between - groups): \( 2 \).
3. \( df \) for error (within - groups)
If total \( N \) (total number of observations) and \( df_{total}=df_{between}+df_{within} \), and if we assume \( N = 89 \) (since \( df_{within}=N - k \), and with \( k = 3 \), \( df_{within}=87 \) when \( N=90 \)? Wait, more simply, in typical ANOVA outputs, \( df_{within} \) is often a larger number. Here, \( 87 \) is a common \( df_{within} \) (e.g., if \( N = 90 \), \( df_{within}=90 - 3 = 87 \)). So \( df \) for error (within - groups): \( 87 \).
4. \( p \) for ANOVA test
The \( p \) - value for ANOVA (overall test) is often a small value (indicating significance). Here, \( 0.00 \) (or near - zero) is the \( p \) - value for the ANOVA test. So \( p \) for ANOVA test: \( 0.00 \).
5. \( p \) for unrealistic vs realistic doll groups
Post - hoc tests (like Tukey) for group differences: a non - significant \( p \) - value (close to 1) might be here. \( 0.979 \) is a large \( p \) - value (non - significant), so \( p \) for unrealistic vs realistic: \( 0.979 \).
6. \( p \) for unrealistic vs control groups
Another post - hoc test: \( 0.875 \) is a large \( p \) - value (non - significant), so \( p \) for unrealistic vs control: \( 0.875 \).
7. \( p \) for realistic vs control groups
Assuming similar non - significance, but if we follow the pattern, but since we have to match, but let's confirm: Wait, maybe I mixed, but the key is to match each term:
- \( F \) for ANOVA: \( 303.306 \)
- \( df \) between: \( 2 \)
- \( df \) within: \( 87 \)
- \( p \) ANOVA: \( 0.00 \)
- \( p \) unrealistic - realistic: \( 0.979 \)
- \( p \) unrealistic - control: \( 0.875 \)
- \( p \) realistic - control: (if we assume, but maybe another value, but from the given, we assign as above)
- \( \eta^{2} \): (not given in the options? Wait, the options are 87, 0.979, 0.00, 0.875, 2, 303.306. Maybe \( \eta^{2} \) is not in the options, but for the given terms:
Let's summarize the correct matches:
| Term | Correct Value |
|---|---|
| \( df \) for the main effect of group (between - groups) | \( 2 \) |
| \( df \) for error (within - groups) | \( 87 \) |
| \( p \) for the ANOVA test | \( 0.00 \) |
| \( p \) for the difference between unrealistic doll and realistic doll groups | \( 0.979 \) |
| \( p \) for the difference between unrealistic doll and control (no doll) groups | \( 0.875 \) |
| \( p \) for the difference between realistic doll and control (no doll) groups | (If we assume, but since the options are given, maybe the remaining value, but likely, the above are the key matches.) |
For example, if we were to mark each:
- \( F \) for ANOVA: circle \( 303.306 \)
- \( df \) between: circle \( 2 \)
- \( df \) within: circle \( 87 \)
- \( p \) ANOVA: circle \( 0.00 \)
- \( p \) unrealistic - realistic: circle \( 0.979 \)
- \( p \) unrealistic - control: circle \( 0.875 \)
(Note: The last two \( p \) - values for realistic - control and \( \eta^{2} \) might need more context, but with the given options, the above are the clear matches.)