Based on the R Square it can be concluded that the linear regression equation obtained predicts adequately the assay based on the passed time. True False

If I want to estimate the regression of a model by using OLS on Eveiws , and I chose the "keep it as general as possible" approach, what tests can I apply through the estimation and inference process to validate the model and the variables?

Plot the linear regression line  y = 3 + 0.5x without using excel with proper labelling

Suppose that the regression model is defined as: y=B1x+u Use the least squares method to estimate the slope of the regression line. Define the objective function that will be used in the estimation. Lastly, enumerate the steps in deriving the estimator of B1

Assuming the model is re-estimated with additional new variable (lagged of LGDP), based on the new estimated results, what is your conclusion about the autocorrelation diagnostic test? If there is diagnostic problem, show how to solve the problem.

An econometrician suspects that the residuals of her model might be autocorrelated. Explain the steps involved in testing this theory using the Durbin–Watson (DW) test

A researcher is hired to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance in miles between home and work for the employees. A sample of 10 employees was chosen and the results are listed in the chart below. Use the proper Data Analysis function in Excel to computethe regression equation needed to predict the number of missed days that could be expected foremployees who live certain distances away from the workplace.  Distance to Work (miles): 1, 3, 4, 6, 9, 10, 12, 14, 14, 18                                    Number of Days Absent: 9, 6, 7, 7, 6, 4, 5, 3, 4, 2

Suppose the regression in Equation is estimated using LoSTR andLoEL in place of HiSTR and HiEL, where LoSTR = 1 - HiSTR is anindicator for a low-class-size district and LoEL = 1 - HiEL is an indicatorfor a district with a low percentage of English learners. What are thevalues of the estimated regression coefficients?

Consider the model Ci= B0+B1 Yi+ ui. Suppose you run this regression using OLS and get the following results: b0=-3.13437; SE(b0)=0.959254; b1=1.46693; SE(b1)=0.0697828; R-squared=0.130357; and SER=8.769363. Note that b0 and b1 the OLS estimate of b0 and b1, respectively. The total number of observations is 2950. The number of degrees of freedom for this regression is A. 2950 OB. 2948 OC. 2952 OD. 2

The least squares regression line for a set of data is calculated to be y = 24.8 + 3.41x. (a) One of the points in the data set is (4, 37). Calculate the predicted value. (b) For the point in part (a), calculate the residual.