List of top Economics Questions on Linear regression

Consider the following population regression equation:

For a sample of employees participating in an annual appraisal, the effect of the participants’ performance on their wages is studied. Information are collected, and variables of interest are defined below:

Let \(Y_t\) be the value of \(Y\) in year \(t\). The natural logarithmic value of \(Y_t\) is regressed on \(t\). A simple linear regression yields the statistically significant estimates of intercept and slope coefficient as \(12\) and \(0.1512\), respectively. The calculated compound annual growth rate of \(Y\) is

The estimated regression equation is \(\hat{y}=60+5X\). What is the slope of this regression equation?

Linear regression model is

The correct stepwise procedure for finding out the optimal solution as per graphical method of LPP would be:
A. Formulate the problem mathematically as on LPP.
B. Find the coordinates of all the corner points of the feasible region.
C. Select the corner point that optimize the value of the objective function.
D. Plot a graph representing all constraints of the problem and determine the feasible region.
E. Find the value of objective function at each of the corner point.
Choose the correct answer from the options given below:

Linear regression model is:

Given the assumptions of the classical linear regression model, the ordinary least square estimators possess some optimum properties-given in the Gauss-Markov theorem. Which of the following is not a part of this theorem?

In the expression
\(Y_i =\hatβ_1+\hatβ_2X_i +\hat{u_i}\)
\(\hat{u_i}\) gives the difference between

You are given the following data for two variables X and Y:
\(\bar{X} = 2.00, \bar{Y}= 4.67\)
Regression coefficient of Y on X = 1.50
What is the estimated value of intercept in the regression of Y on X?

For a level curve of f(x, y) = x²y, what is the value of \(\frac{dy}{dx}\)?

One of the assumptions of the classical linear regression model is that all the values of the explanatory variable X must

What is the number of degrees of freedom of the residual sum of squares in a simple bivariate linear regression with 100 observations?