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- The estimated regression models having a different number of explanatory variables are compared on the basis of _____. Select one: a. Chi squared -statistic b. Adjusted R squared-statistic c. R squared-statistic d. None of the aboveEnumerate the 10 assumptions of the classical linear regression model (CLRM) and discuss its importance in econometrics analysis.Investigate what factors determine the number of times a person logs into Facebook per week. It is argued that these four factors are important: number of friends, age in years, whether the person is employed, and whether the student has a Twitter account. The function is: FACEBOOK LOGIN=f(FRIENDS,AGE,EMPLOYED,TWITTER) With this functions and variables in mind: Perform necessary tests and analysis to determine the validity of the regression attached in the below table and function provided The tests and analysis must be broken down into two sections namely: tests that are possible with the given regression’s information and tests that should be conducted but are not possible with the given information. For the tests that are possible please conduct them at a 5% significance level and for those that are not possible only mention their names without any further details
- All the regression assumptions lie on the residuals, for both simple and multiple regression. True or False?In regression analysis, a common metric used in assessing the quality of the model being used to fit the data is known as the R-squared coefficient. Explain the R-squared coefficient. What is the difference between the R-squared and adjusted R-squared coefficients?True or False For a linear regression model including only an intercept, the OLS estimator of that intercept is equal to the sample mean of the independent variable.
- Consider a data set with 15 observations and consider a multiple linear regression model with 7 in-dependent variables. Assume you have estimated the model and you find that SST = 1,325 and SSR = 794.The assumption that the error terms in a regression model follow the normal distribution with zero mean and constant variance is required Select one: Estimation of the regression model using OLS method Point estimation of the parameters Hypothesis testing and inference Inference One of the assumption of CLRM is that the number of observations in the sample must me greater the number of Select one: Dependent and independent variable Dependent Variable Regressor Regressands Information about numerical values of variables from period to period is Select one: Time series data Pooled data Panel data Cross section data Multicollinearity is essentially a Select one: Sample phenomenon or population phenomenon sample phenomenon Sample phenomenon and population phenomenon Population phenomenon The larger the standard error of the estimator, the greater is the uncertainty of estimating the true value of the unknown parameters. This statement is Select one: True FalsePlease type out the correct answer ASAP with proper explanation of why true n why false within 40 50 minutes. Will give you thumbs up only for the correct answer. Thank you .... Suppose we estimate a regression model that is linear in the parameters, the sample is obtained through random sampling, is no perfect collinearity, the errors have zero conditional mean and are homoskedastic, and the sample size is large. Even under these conditions, the OLS estimators of the parameters are not normally distributed, even approximately, if the regression errors are not normally distributed. A. True B. False
- No written by hand solution Consider the following data: x⎯⎯x¯ = 20, sx = 2, y⎯⎯y¯ = −5, sy = 4, and b1 = 0.40. Which of the following is the sample regression equation? Multiple Choice yˆ = −13 − 0.40x yˆ= −13 + 0.40x yˆ = 3 − 0.40x yˆ = 3 + 0.40xThe regression equation to predict sales based on temperature is: Predicted sales = -2419.01+ 98.02 (temperature). A correct interpretation of the slope would be that 1. as temperature goes up by 1 degree, sales are predicted to go down by 2419.01. 2. as temperature goes down by 1 degree, sales are predicted to go up by 2419.01. 3. as temperature goes up by 1 degree, sales are predicted to go down by 98.02. 4. as temperature goes up by 1 degree, sales are predicted to go up by 98.02. 5. None of the answer choices provides a correct interpretation of the slope.Please no written by hand The assumption of normally distributed errors means that... A. errors can be ignored when doing regression modelling. B. the OLS estimators can also be assumed to be normally distributed since they are a linear functions of the errors. C. the OLS estimators can also be assumed to be normally distributed since they are BLUE. D. the OLS estimators can also be assumed to be normally distributed since they are minimum variance. E. the regression model will not be subject to specification error.