Lecture 13

Question 1

define robust regression

Answer 1

is a form of regression analysis designed to overcome some limitations of traditional parametric and non-parametric methods. Regression analysis seeks to find the relationship between one or more independent variables and a dependent variable.

Question 2

what is the significance of results, if 95% confidence interval has both negative and positive values?

Answer 2

the result is insignificant

Question 3

what is the significance of results, if 95% confidence interval has only negative or positive values?

Answer 3

the results are significant

Question 4

where is the dependent variable indicated in research papers?

Answer 4

in the title of the table

Question 5

does robust regression address issues of heterogeneity of variance? and if not, how can we address it?

Answer 5

No it does not. This problem can be addressed by using functions in the sandwich package after the lm function.

Question 6

how outliers will alter the data?

Answer 6

Outliers in the data will result in overestimated or underestimated regression coefficients, The relationship between the dependent and independent variables will be incorrectly estimated

Question 7

if we cannot remove outliers, what method should be used?

Answer 7

robust regression models should be used.