Use the data in PNTSPRD.RAW for this exercise.
(i) The variable sprdcvr is a binary variable equal to one if the Las Vegas point spread for a college basketball game was covered. The expected value of sprdcvr, say p., is the probability that the spread is covered in a randomly selected game. Test H1: ( ( .5 against H1 : ( + .5 at the 10% significance level and discuss your findings. (This is easily done using a t test by regressing sprdcvr on an intercept only.)
(ii) How many games in the sample of 553 were played on a neutral court?
(iii) Estimate the linear probability model
sprdcvr = (0 + (1 favhome + (2 neutral + (3 fav25 + (4 und25 + u
and report the results in the usual form. (Report the usual OLS standard errors and the heteroskedasticity-robust standard errors.) Which variable is most significant, both practically and statistically?
(iv) Explain why, under the null hypothesis H0: (1 = (2 = (3 = (4 = 0, there is no heteoskedasticity in the model.
(v) Use the usual F statistic to test the hypothesis in part (iv). What do you conclude?
(vi) Given the previous analysis, would you say that it is possible to systematically predict whether the Las Vegas spread will be covered using information available prior to the game?