Price=0+1 Rain+2MaxTemp+3Tuesday+4Wednesday+5Thursday+6Friday+7Saturday+8Sunday+9Black +10 Hispanic +11 Asian

Plugging the parameter estimates into the inverse demand function:

Price=16.33+0.083 Rain+0.0179MaxTemp+0.31Tuesday+0.57Wednesday+0.78Thursday+2.15Friday+11.74Saturday+8.45Sunday-0.0796Black+0.094 Hispanic-0.1979 Asian

In the specification above, the baseline is a responder who answered on Monday and whose race is white. The print out of the results will show you the estimated effect of each variable on ticket price. You will see, for example, that a 1 degree increase in temperature would increase the ticket price by $0.0179. You will see that prices on Saturday are $11.74 higher than on Mondays, whereas Friday prices are $2.15 higher than Mondays. Turning to the race variables, we see that black respondents paid $0.07 less for their tickets than whites, Hispanics paid $0.09 more than whites, and Asians paid about $0.20 less than whites.

The regressions also give us standard errors for each of these estimated coefficients. For example, the standard error on black is 0.087218. The -0.079643 is the point estimate, and we can construct a 95% confidence interval using the standard error times 1.96:[1] Upper limit = -0.079643 + 1.96*0.087218 = 0.09130428 Lower limit = -0.079643 - 1.96*0.087218 = -0.2505903

The 95% confidence interval runs from $0.09 to -$0.25, and because this range passes over zero we cannot reject the null hypothesis that black zoo patrons pay the same ticket prices as whites. The point estimate suggests they actually pay a little bit less.

a).Compute the upper limit for Hispanics.

b). Compute the lower limit for Hispanics.

c).True or False: At a 95% confidence interval, we cannot reject the null hypothesis that Hispanic patrons pay the same ticket prices as whites.

[1] You will do this eventually in V506, and in there you will learn that the 1.96 used in the calculation came from a t-table with a two tail distribution.