Two new variables, the market value of the firm (a measure of firm size, in millions of dollars) and stock return (a measure of firm performance, in percentagepoints), are added to the regression:In(Earnings) = 3.86 – 0.28Female + 0.37In(MarketValue) + 0.004Return,(0.03) (0.04)(0.004)(0.003)n = 46,670, R = 0.345.If MarketValue increases by 1.88%, what is the increase in earnings?If MarketValue increases by 1.88%, earnings increase by 0.70 %(Round your response to two decimal places.)The coefficient on Female is now – 0.28. Why has it changed from the first regression?O A. Female is correlated with the two new included variables.O B. MarketValue is important for explaining In(Earnings).O C. The first regression suffered from omitted variable bias.OD. All of the above.Assume that the coefficient estimated in the second regression is correct. Forget about the effect of the Return variable, whose effect seems small and statisticallyinsignificant. Calculate the correlation between Female and In(MarketValue) using the omitted variable bias equation.Let X = Female, u = MarketValue, and= 0.53OxThe correlation between Female and In(MarketValue), exu, is. (Round your response to three decimal places.)

Answered: D. All of the above. ume that the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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1. Plot a scatter diagram (for non-PHStat2 users, just find scatter plot in "Insert" tab in Excel). Does it appear that there is a linear relationship between advertising cost and sales? Why or why not? 2. Compute the correlation coefficient and INTERPRET. 3. From the scatter plot, is it reasonable to perform simple linear regression between the two variables? Why or why not? 4. What is a reasonable choice for the dependent and independent variables. Why? NOTE: please answer ASAP. I really need help.
4. A study was conducted to investigate the relationship between the size of a house (in square feet) and the selling price of a house (in dollars). The response variable is price in dollars, and we want to study if the covariate of the square footage helps explain the response. A random sample of 522 houses was used, and the linear regression output from R is below. price sqft, data = house) 1m (formula = Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -81432.946 11551.846 -7.049 5.74e-12 *** sqft 158.950 4.875 32.605 <2e-16 *** Residual standard error: 79120 on 520 degrees of freedom Multiple R-squared: 0.6715, Adjusted R-squared: 0.6709 a. Write out the estimated linear equation. What is the estimated expected selling price of a house that is 2000 square feet? b. Does the intercept have a useful interpretation in this study? Why or why not. c. Interpret the slope estimate in context of the model.
Choose all that apply when describing R2. (Hint: 5 options are correct) (Select all that apply.) Can be inflated by adding more variables. O Can be inflated by removing variables. Referred to as the coefficient of detemination or coefficient of multiple determination. Is used to determine the fit of a model. Represents the percent of variability in y that can be explained by the model. In simple linear regression, it is equal to the correlation coefficient 2. O Only describes the relationship between quantitative variables. O Is only used in multiple linear regression. SSres SSreg SStotal SStotal
Write the formula for the estimated regression line and interpret the slope of the estimated regression line, the intercept of the estimated regression line- Is it meaningful?, and the estimated R2. Based on the fitted regression model, what is the predicted ATST for a child who is 7 years old? What is the correlation between AGE and ATST? Does the residual plot suggest that the fitted regression line is inappropriate for these data? Explain why or why not. Suppose that a new subject is added to the study data and that subject is 12.5 years old with an ATST of 580 minutes. If the regression model were to be refit with this additional data point, would the new slope be greater than or less than -14.041? Justify your response.
Exercise 6. Regression Fallacy. Historically, scores on the two midterms had a correlation of 0.48. Suppose that Jeri scored 2.1 standard deviations below the mean on the first midterm. (a) How many standard deviations [above or below?] the mean would you predict for her second midterm?
The fish in my pond have mean length 10 inches and mean weight 4 pounds. The correlation coefficient of length and weight is .9. If the length of a particular randomly selected fish is reported to be 10 inches, then what should we predict for the weight of that fish using simple linear regression? 4 10 2.5 NOT ENOUGH INFORMATION GIVEN NONE OF THE OTHERS
Prev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an Item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 3 of 6: Find the estimated value of y when x = 33. Round your answer to three decimal places. Table Copy Data Next
Find correlation coefficient between the exchange and expenditure from the datagiven below: Obtain the regression equation of exchange on expenditure expenses and find out theexpected exchange of a firm when expenditure is Rs. 25 lakhs. Also find coefficientof determination and interpret your result.
A researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis (Pearson's Correlation)
3. Regression analysis breaks scores on the DV into... (explain and give equations)
Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next
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