Dependent Variable: COURSE_EVAL Method: Least Squares Date: 12/02/17 Time: 00:48

Question

Dependent Variable: COURSE_EVAL Method: Least Squares Date: 12/02/17 Time: 00:48 Sample: 1 463 Included observations: 463 Variable Coefficient Std. Eor t-Statistic Prob. 4.168530 0.141806 29.39593 0.0000 4.981359 0.0000 0.183234 0.051069 -3.587978 0.0004 0.076414-2.217254 0.0271 0.243840 0.107013 -2.278602 0.0232 18 0.8845 0.633000 0111415 5.681456 0.0000 0.001954 0.002666 -0.733072 04639 0159209 0.031961 BEAUTY FEMALE MINORITY NNENGLISH INTRO ONECREDIT AGE 0.007949 0.054700 0.1453 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic 0.155647 Mean dependent vu 0.142657 S.D. dependent yar 0.513766 Akaike info criterion 120.0996 Schwarz criterion 344.581 Hannan-Quinn criter. 11.98202 Durbin-Watson stat 0.000000 3.998272 0.554866 1.523029 1.594523 1.551174 1.514519 Prob(F-statistic) Given: Beauty Female teaching evaluation score, on a scale of 1 very unsatisfactory) to 5 (excellemt) rating of instructor physical appearance by a panel of six students, averaged and shifted to have a mean of zero l if female, 0 otherwise 1 if instructor is non-White, 0 otherwise 1 is the instructor is not a native English speaker, 0 otherwise 1 if course is introductory level, 0 otherwise 1 if course is single-credit elective, 0 otherwise professor's age Age This data was taken from 463 courses at UTAustin for the years 2000-2002 Interpret the regression in detail. Do you think that it might be advisable to add some interactive terms? Why?

Explanation / Answer

Yes, it might be advisable to look at some interaction terms. For e.g. –

1. An interaction between Female and Intro course. We will get to know how this females teaching intro course affects the eval score.

2. An interaction between NNENGLISH and ONECREDIT - This will help us in knowing if non-english professors teaching single credit score still witness a negative association with course eval score.

One can likewise think of other meaningful interaction terms that can give us some interesting results.

Variable Coefficient's interpretation Beauty A more beautiful teacher has positive association with on teaching eval score. This result is statistically significant at all critical levels. Female A female teacher is likely to have a negative association with the evaluation score. This result is statistically significant at all critical levels. Minority Likewise a non-white teacherhas a negative effect on eval score. This result is significant at 5% critical level NNEnglish A non-english teacher is again likely to have a lower evaluation score. This result is significant at 5% critical level Intro This variable is statistically insignificant. It appears that intro courses have little effect on evaluation score. Onecredit A single credit course has a statistically significant effect on the eval score. The association with eval score is positive. Age Professor's age is not a significant variable. It appears that eval score has little connection with age of the teacher.

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