Consider the regression model: yi = β0 + β1Xi + εi for…. i = 1
Where the dummy variable (0 = failure and 1 = success). Suppose that the data set contains n1 failure and n2 successes (and that n1+n2 = n)
Consider the regression model: yi = β0 + β1Xi + εi for…. i = 1 Where...
We run the following linear regression model in Excel (or any other softwares) Yi = β0 + β1Xi + β2Wi + εi , where i = 1, 2, . . . , 100. The results suggest that the slope on Xi is 97.28 with t-statistics 0.91, and the slope on Wi is 15.81 with t-statistics 11.39. What does it tell us?
Consider the regression model given by: Yi = βo + β1Xi + β2Zi+ ui Suppose that an econometrician wishes to test the null hypothesis given by: Ho: β1 + β2 = 1 Use this null hypothesis to specify a restricted form of the regression model (in a form that may be estimated using an OLS estimation procedure). State the equation that you could estimate as the restricted version of this model.
Consider the regression model given by: Yi = βo + β1Xi + β2Zi+ ui Suppose that an econometrician wishes to test the null hypothesis given by: Ho: β1 + β2 = 0 Use this null hypothesis to specify a restricted form of the regression model (in a form that may be estimated using an OLS estimation procedure). State the equation that you could estimate as the restricted version of this model.
Consider the linear regression model Yi = β0 + β1 Xi + ui Yi is the ______________, the ______________ or simply the ______________. Xi is the ______________, the ______________ or simply the ______________. is the population regression line, or the population regression function. There are two ______________ in the function (β0 & β1 ). β0 is is the ______________ of the population regression line; β1is is the ______________ of the population regression line; and ui is the ______________. A. Coefficients...
1. If a true model of simple linear regression reads: yi −y ̄ = β0 +β1(xi −x ̄)+εi for i = 1, 2, · · · , n, showβ0 =0andβˆ0 =0. (1pt) (hint: use the formula of estimator βˆ0 = y ̄ − βˆ1x ̄.)
3. Give the population model Yi = β0 + β1Xi + ui T he variance of β1 will (BLANK) as the variation in x decreases, and it will decrease if we (BLANK) the variance of the error term. a) increase. increase b) increase. decrease c) decrease. decrease d) decrease. increase
Section 1: True/False, & explain why three or more sentences: 2. In the regression model Yi = β0 + β1Xi + β2Di + β3(Xi × Di) + ui, where X is a continuous variable and D is a binary variable, β3 has no meaning since (Xi×Di) = 0 when Di= 0.
A simple linear regression model is given as follows Yi = Bo + B1Xi+ €i, for i = 1, ...,n, where are i.i.d. following N (0, o2) distribution. It is known that x4 n, and x = 0, otherwise. Denote by n2 = n - ni, Ji = 1 yi, and j2 = 1 1. for i = 1, ... ,n1 < n2 Lizn1+1 Yi. n1 Zi=1 1. Find the least squares estimators of Bo and 31, in terms of...
Consider the following formulations of the 1 variable regression model: Y = β0 + β1x + u and Y = α0 + α1(x − ¯x) + a a) would the estimates of β0 and α0 the same? Explicitly shows this by deriving the estimates. b) What about β1 and α1 ? c) In the regression Y = β0 +β1x+u suppose we multiply each X value by a constant, say, 2. Will it change the residuals and fitted values of Y?...