Answer Happy

2 Consider the following regression table from simple regression: In (no.of.passengers;) = $₁ + ß₂ln (fare,) + ₁, where all the classical assumptions are satisfied, including the normality of the error term dis- tribution. Note, you cannot resort to the large sample theory in this case because the sample size is NOT large enough. Call: In (formula log(no_paasangars) log(fare), data airfare data) Residuals: Min 10 Median 30 Max -5.1467 -0.6367 -0.0515 0.6074 2.8708 Coefficients: Ectinate Std. Error t value Pr(>1t|) 0.5519 14.113 14.1132-16 *** (Intercept) 7.7884 log(fare) -0.3589 0.1087 -3.301 0.00108 ** --- Signif. codea: 0¹ 0.001 a 0.01 0.05 0.11 Residual standard error: 0.9825 on 458 degrees of freedom Multiple R-aquared: 0.02141, Adjustad R-aquared: 0.01945 1. You want to test the null hypothesis Ho: ₁ = 8 vs. the alternative hypothesis H₁ : ₁ 8. You constructed a test statistic of the following form: 7.7884 - [4] T= 0.5519 Fill in the missing number in [a]. (5pts) [ ] (a) -0.1087 (b) 0.1087 (c) -0.3589 (d) 0.3589 (e) 0 (f) -1 (g) 1 (h) -8 2. Interpretation of the $2 is such that one percent increase of fare; will induce, on average, 0.3589 percent increase of no.of.passenger; variable. True or False? [ ] (a) True (b) False 3. You can reject the null hypothesis of Ho: 2 = 0 at 0.1% significance level. True or False? [1 (a) True (b) False 4. The value of the correlation coefficient in(no of passengers), Infare,) is 0.02141. True or False? [] (a) True (b) False 5