Economics 306 C L I C K E R S Practice Which of the following is not true about the t distribution A It has more area in the tails and less in the center than does the normal distribution B It is used in place of the normal distribution when the population standard deviation is known C It is bell shaped and symmetrical D As the number of degrees of freedom increases the t distribution approaches the normal distribution Practice All else equal if the variance of X increases by a factor of 4 the correlation coefficient between X and Y will A Increase by a factor of 4 B Decrease by factor of 4 C Increase by a factor of 2 D Decrease by a factor of 2 Practice You have collected data on the average weekly amount of studying time T and grades G from students at your college Changing the measurement of time from minutes into hours has the following effect on the sample correlation coefficient r A decreases the correlation coefficient by dividing the original correlation coefficient by 60 B results in a higher value of r C cannot be computed since some students study less than an hour per week D does not change the value of r Practice Suppose the covariance of X and Y is negative As X decreases the expected value of Y will A decrease B increase C be unchanged Practice The reason why estimators like the s have a sampling distribution is that A economics is not a precise science B individuals respond differently to incentives C in real life you typically get to sample many times D the values of the Y differs across random samples samples The OLS errors i are defined as follows i 0 1Xi A B Yi 0 1Xi C Yi D Yi i 2 Answer c When the estimated intercept coefficient in a regression model 0 is zero then A r2 0 B E 0 0 C 0 D The sample regression line passes through Y the origin In the simple linear regression model described thus far the regression slope A indicates by how many percent Y increases given a one percent increase in X B when multiplied with the explanatory variable will give you the predicted Y C indicates by how many units Y increases given a one unit increase in X D represents the elasticity of Y with respect to X When the estimated slope coefficient in the simple regression model is zero then 1 A r2 0 B 0 r2 1 Y C D r2 SSR SST 1 The following statements about the sample regression function are true except a R2 1 SSE SST b 0 i iX c i d SST Y 0 iY 2 True a or False b X i X Y Y i X i X Y i True You run a regression with 30 observations and find the R2 43 SST 1000 and the variance of X is 225 What is SSE A 430 B 520 C 570 D 690 Continuing with the previous problem You run a regression with 30 observations and find the R2 43 SST 1000 and the variance of X is 225 We ve found that SSE 570 What is the SD of the Slope Coefficient A 003 B 005 C 034 D 055 Consider the following sample regression line T 80 1 2 28ST where T is the score on a test and ST is the number of hours studying for it The null hypothesis is that the slope coefficient equals zero You are told that the t statistic on the slope coefficient is 4 38 What is the standard error of the slope coefficient A 0 52 B 1 96 C 1 92 D 1 52 Suppose we want to study the effect of cigarette consumption on age of death We let Y age of death and X1 lifetime cigarette consumption Consider the variable X2 Body Mass Index If X2 is in the PRF for Y what will be the likely bias from omitting X2 from the regression of Y on X1 A Positive B Negative C Zero Suppose we want to study the effect of cigarette consumption on age of death We let Y age of death and X1 lifetime cigarette consumption Consider the variable X2 Days per week of exercise If X2 is in the PRF for Y what will be the likely bias from omitting X2 from the regression of Y on X1 A Positive B Negative C Zero Suppose we want to study the effect of cigarette consumption on age of death We let Y age of death and X1 lifetime cigarette consumption Consider the variable X2 Cholesterol Level If X2 is in the PRF for Y what will be the likely bias from omitting X2 from the regression of Y on X1 A Positive B Negative C Zero You regress Y on two explanatory variables X1 and X2 Suppose the variance of the regression is equal to 1600 and the variance of X1 1 There are 401 observations What is the variance of when X1 and X2 have correlation r 95 1 a 34 25 b 41 03 c 45 67 d 52 64 You run a regression of Y on 3 independent variables You want to test 2 1 3 2 Which of the following regressions will allow you to test this 1 0 hypothesis directly with a t test a Y b Y c Y d Y 2 2 2 X 2 X X 2 X 2 X 1 X 2 X 2 X X X X 1 X 2 2 1 0 1 2 0 1 1 0 2 1 3 3 3 3 3 3 X X X 3 X 3 1 1 X X X 1 X 1 Answer b You run a regression of Y on 3 independent variables You want to test 0 4 2 H 3 Which of the following regressions will allow you to test 6 1 2 this hypothesis directly with a t test a Y b Y c Y d Y X 1 0 2 X 2 1 X 2 0 2 1 X 2 2 X 3 3 X 3 2 3 X 3 3 X 3 3 2 0 Answer d X 2 2 X 2 X 2 X X 1 X X 1 X 1 1 0 1 X 3 1 X 3 X 1 3 X 3 1 1 You are running a regression with 10 independent variables You want to test whether 4 of those variables jointly equal 0 You have 98 observations You calculate unrestricted and restricted versions of the regression and SSEu 625 SSEr 705 What is the F Statistic a 2 04 b 2 78 c 3 35 d 3 66 What is the denominator of the F Statistic a The Variance of the Regression b The Variance of c The Variance of d The Small Sample Bias Delimitter Function 0 1 Suppose you run a regression of annual wage on education and find the value of the coefficient on education to be 3 5 …