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Unformatted text preview: as a r esult of log transformation.
After log transformation, the problem of lack of variance constancy seems to have
improved. The qqplot and the scatterplot are pretty similar before and after
transformation. We still have outliers after transformation. Point 223 is still a problem.
• L ist any weaknesses that you find in the model based on log
t ransformations.
Please see above. Question four . Refer to the article that was posted on week five of CCLE
Title of the article: The Career Plans of ScienceTalented Rural
Adolescent Girls
Answer the following questions:
a ) List the predictors and the outcomes. Are they quantitative or
q ualitative?
The predictors include Science GPA, Friends' support, Number of science/math activities,
Number of nonscience activities, Mothers' perceptions of child's science ability,
Mothers' valuing of science for females, Adolescents' interest in biology, Adolescents'
interest in physical science. The outcome variables are adolescent’s preference for any
science career, for physical science, for health science professions, and human services
professions. They are considered quantitative since they have computed mean and
standard deviation for all of them.
b ) In the last row of table two, you see 0.39**
0.39 shows the coefficient of correlation between adolescent’s interest in physical science
and mother’s valuing of science for females.
• W hat is the null hypothesis underlying this test (i.e. 0.39**) in
s ymbols
a nd in words within context?
The null hypothesis is that the coefficient of correlation between adolescent’s interest in
physical science and mother’s valuing of science for females is equal to zero.
H0: ρ = 0
• D o you reject or fail to reject the null and why? What do you
c onclude?
0.39** means that we reject the null hypothesis at P = 0...
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This note was uploaded on 02/05/2014 for the course STAT 101A taught by Professor Mahtashesfandiari during the Fall '11 term at UCLA.
 Fall '11
 MahtashEsfandiari
 Statistics

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