gaussmarkov: Knowledge Quiz Question about Gauss-Markov Assumptions
gaussmarkovUnder the assumptions of the Gauss-Markov theorem the errors of a linear regression model need to be:
Under the assumptions of the Gauss-Markov theorem the errors of a linear regression model need to be uncorrelated, homoscedastic, and with mean zero.
- True. The errors need to be homoscedastic with finite variance.
- False. No distribution assumption is needed.
- False. Only their conditional expectation needs to be zero.
- True. The errors need to be uncorrelated.
- False. No distribution assumption is needed.
Under the assumptions of the Gauss-Markov theorem the errors of a linear regression model need to be:
Under the assumptions of the Gauss-Markov theorem the errors of a linear regression model need to be uncorrelated, homoscedastic, and with mean zero.
- False. No distribution assumption is needed.
- False. Only their conditional expectation needs to be zero.
- True. The errors need to be homoscedastic with finite variance.
- False. No distribution assumption is needed.
- True. The errors need to be uncorrelated.
Under the assumptions of the Gauss-Markov theorem the errors of a linear regression model need to be:
Under the assumptions of the Gauss-Markov theorem the errors of a linear regression model need to be uncorrelated, homoscedastic, and with mean zero.
- False. Independence is not assumed, only lack of correlation.
- False. No distribution assumption is needed.
- False. No distribution assumption is needed.
- True. The errors need to be uncorrelated.
- True. The errors need to be homoscedastic with finite variance.
Demo code:
library("exams")
set.seed(403)
exams2html("gaussmarkov.Rmd")
set.seed(403)
exams2pdf("gaussmarkov.Rmd")
set.seed(403)
exams2html("gaussmarkov.Rnw")
set.seed(403)
exams2pdf("gaussmarkov.Rnw")