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?
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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?
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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 aboveWhich of the following is a consequence of severe multicollinearity in a regression model? A. High standard errors for the estimated coefficientsB. Lower standard errors for the estimated coefficientsC. The OLS estimator becomes biasedD. The dependent variable becomes constantAs the number of relevant independent variables in a regression increases, the R-squared of a regression Select one: a. exhibits greater heteroskedasticity b. increases c. decreases d. stays constant
- Question 15 When the R2 of a regression equation is very high, it indicates that all the coefficients are statistically significant. the intercept term has no economic meaning. a high proportion of the variation in the dependent variable can be accounted for by the variation in the independent variables. there is a good chance of serial correlation and so the equation must be discarded.What is the functional form of this equation? What are the advantages and limitations of this functional form? Interpret precisely the coefficients of Px and Py in the regression.A simple regression analysis to estimate the demand for Chick-fil-A’s new premium super-sized spicy chicken sandwich is Q= 48-2p. If Chick-fil-A sets the price at $12 and Q=20, calculate the regression’s error term? Also, list five assumptions of the classical linear regression model.
- In a regression problem with 1 output variable and with a total number of 100 possible input variables, what is the number of all possible models with three input variables?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.All the regression assumptions lie on the residuals, for both simple and multiple regression. True or False?
- XYZ company is interested in quantifying the impact of consumer promotions on the sales of its packaged food product. XYZ has historical data on the following variables for 38 weeks: • Sales: Weekly sales volume in thousands of units.• Prom: Weekly spending on consumer promotions in thousands of Dollars" "A regression analysis was applied to XYZ historical dataset. The dependent variable is weekly Sales and the independent variables are weekly Prom and weekly Lagged Prom (i.e., last week Prom). This is a summary of the regression output:Sales = 0.80 + 1.20*Prom - 0.40*Lag(Prom) • R-squared=0.85• F-Statistic=23.83• p-value=0.001 (for the overall regression)•All regression coefficients are statistically significant at the 5% level." A. What will be the predicted sales volume ? B. What is the gross margin of this net volume impact due to $1000 spending per week on consumer promotions, if brand makes $2.20 gross margin per unit . C. What is the ROI of this promotion? D. What is predicted…The appropriate statistic to examine the goodness of fit of a two-variable regression model is _____. Select one: a. t-statistic b. F-statistic c. R2-statistic d. Chi-square statisticThe controller of Chittenango Chain Company believes that the identification of the variable and fixed components of the firm’s costs will enable the firm to make better planning and control decisions. Among the costs the controller is concerned about is the behavior of indirect-materials cost. She believes there is a correlation between machine hours and the amount of indirect materials used.A member of the controller’s staff has suggested that least-squares regression be used to determine the cost behavior of indirect materials. The regression equation shown below was developed from 40 pairs of observations.S = $200 + $9H where S = Total monthly cost of indirect materials H = Machine hours per month The estimated cost of indirect materials if 900 machine hours are to be used during a month is $8,300 (Assume that 900 falls within the relevant range for this cost equation.) The high and low activity levels during the past four years, as measured by machine hours, occurred…