A counseling psychologist hypothesizes that more perceived
femininity predicts less perceptions of a traumatic event.
Participants in a study are asked to rate the combat situation of
female soldiers that recently returned from combat and suffered
from depression. Participants rated the combat situation with
respect to how traumatic they believe it was and assessed how
feminine they perceived the female soldier to be. Higher scores
indicate more trauma and femininity, respectively, on the ratings
of the situation as traumatic and perceptions of being feminine.
The data are below. What can the psychologist conclude with α =
0.01?
| Trauma | Feminine |
|---|---|
| 6 7 5 9 8 9 10 6 7 8 9 |
3 4 4 3 5 4 5 5 4 3 5 |
a) What is the appropriate statistic?
Slope
Chi-Square
Compute the statistic selected above:
b) Compute the appropriate test statistic(s) to
make a decision about H0.
(Hint: Make sure to write down the null and alternative hypotheses
to help solve the problem.)
p-value =
A: The appropriate statistic is slope.
B:
The regression result between the two variable is below
Call:
lm(formula = Trauma ~ Feminine)
Residuals:
Min 1Q Median 3Q Max
-2.60526 -0.93421 0.05263 1.22368 2.05263
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.2368 2.5745 2.423 0.0385 *
Feminine 0.3421 0.6178 0.554 0.5933
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’
1
Residual standard error: 1.624 on
9 degrees of freedom
Multiple R-squared: 0.03294, Adjusted R-squared:
-0.07451
F-statistic: 0.3066 on 1 and 9 DF, p-value: 0.5933
Clearly the slope is positive 0.3421 and insignificant so we can't reject reject our Null hypothesis in favor of alternative that the slope is negative. Hence, there's no significant effect of feminine score.
A counseling psychologist hypothesizes that more perceived femininity predicts less perceptions of a traumatic event. Participants...
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