After collecting data over two years for every one of the 162 LA Dodgers home games of the combined 2000 and 2001 seasons, you run the following regression:
Attend = 15,005+ 201*Temperat+ 465*DodgNetWin + 92*OppNetWin
(8,770) (121) (169) (26)
+ 9647*DFSaSu + 1328*Drain +1609*D150m +271*Ddiv - 978*D2001;
(1505) (3355) (1819) (1,184) (1,143)
R2=0.416, SER = 6,983
where Attend is announced stadium attendance, Temperat it the average temperature on game day, DodgNetWin are the net wins of the Dodgers before the game (wins-losses), OppNetWin is the opposing team's net wins at the end of the previous season, and DFSaSu, Drain, D150m, Ddiv, and D2001 are binary variables, taking a value of 1 if the game was played on a weekend, if it rained during that day, if the opposing team was within a 150 mile radius, if the opposing team plays in the same division as the Dodgers, and if the game was played during 2001, respectively. Numbers in parentheses are heteroskedasticity- robust standard errors.
To test whether the effect of the last four binary variables is significant, you have your regression program find out the relevant F-statistic, which is 0.295. What is the null hypothesis of test you run and what is the critical value? Would you reject the null?