1.
lm(EARNINGS~S+EXP) (in R),
the underlying assumption was that EARNINGS is a normally distributed random variable with an expected value given by a constant, but unknown value (represented by the Greek letter "mu") that we are trying to estimate.
True or False?
2.
In our typical simulation program, when we save some number like 1,000 or 10,000 replications for some statistic like a t-ratio or an F-statistic, the purpose of a summary command such as
mean(abs(ts) > qt(.975,df) ) or check = abs(ts > qt(.975,df)
mean(check),
where df denotes degrees of freedom, is to determine whether the hypothesis tested is false because the mean of check is less than 0.05.
True or False?
1) True
Earning is a response variable which is normally distributed random variable. And we need to find the estimates of parameters in the regression model which will lead to the expected value of earning referred as mu
2) False
Check is a binary variable which only tells True or False. If check is true then mean(check) = 1 and if check is False then mean(check) = 0
Hence we can't say that mean of check is less than 0.05
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