A statistical analyst carried out an investigation of the association of gender
ID: 2935761 • Letter: A
Question
A statistical analyst carried out an investigation of the association of gender and teaching evaluations at a university. They undertook exploratory analysis of the data and carried out a number of bivariate comparisons. The multiple items on the teaching evaluation were consolidated to a single measure based on these exploratory analyses. They used this information to construct a multivariable regression model that found evidence for biases. What issues might arise based on such an analytic approach?Explanation / Answer
The major issue that may come in this multiple regression model is the issue of multicollinearity, which results in biased estimates of the regression co-efficients. Multicollinearity is nothing but the correlation between the independent variables. We should choose the variable in such a way that the correlation between the dependent and independent variable is very high but the correlation between the dependent variables should be as low as possible. Here it may happen one or fee of the other independent variables are somehow correlated with gender.
Another one is the unit of measurement, before carrying out multivariate regression, we should first bring all the continuous variables under same unit i.e. we have to standardize the variables first.
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