Could you please provide me the raw data set in .csv or .xls format so that I can solve it properly, otherwise I am giving you the R code.
Y=c(...) #current EPS
X1=c(...) #Total Assets
X2=c(...) #Previous EPS
X3=c(...) #Previous ROAA
X4=c(...) #Previous ROAE
summary(lm(Y~X1+X2+X3+X4))
c. Option B.
And all the remaining answers would be given in the R- Console.
A fnance executve would ike to determine if a relationship exists between the current earnings per share (EPS) of...
*ANSWERS IN BOX ARE INCORRECT* Consider the following ANOVA table for a multiple regression model. Complete parts a through e below. Source Regression 3 3,600 1200 20 Residual 35 2,100 60 Total df SSMSF 38 5,700 a. What is the size of this sample? n41 b. How many independent variables are in this model? c. Calculate the multiple coefficient of determination. R0.5882 Round to four decimal places as needed.) d. Test the significance of the overall regression model using α=0.05...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
For this assignment I have to analyze the regression (relationship between 2 independent variables and 1 dependent variable). Below is all of my data and values. I need help answering the questions that are at the bottom. Questions regarding the strength of the relationship Model: Median wage (y) = 40.3774 - 2.0614 * Population + 0.0284 * GDP Predictor Coefficient Estimate Standard Error t-statistic p-value Constant B0 40.3774 1.1045 36.558 0 Population B1 -2.0614 0.5221 -3.948 0.0003 GDP B2 0.0284...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
An agency examined the relationship between the ozone level (in parts per million or ppm) and the population (in Dependent variable is: Ozone millions) of cities. Part of the regression analysis is shown to the right. Complete parts a and b below. R squared-84.3% s 5.418 with 16-2 14 df Coeff 18.162 6.501 SE(Coeff) 2.098 2.093 Variable Intercept Population a) It is-suspected that the greater the population of a city, the higher its ozone level. Is the relationship statistically significant?...
An agency examined the relationship between the ozone level (in parts per million or ppm) and the population (in millions) of cities. Part of the regression analysis is shown to the right. Complete parts a and b below. Dependent variable is: Ozone R squaredequals82.2% s=5.158 with 16-2=14 df Variable Coeff SE (Coeff) Intercept 18.769 2.311 Population 6.701 2.027 a) It is suspected that the greater the population of a city, the higher its ozone level. Is the relationship statistically...
QUESTION 27 Q27. A manager at a local bank analyzed the relationship between monthly salary (y, in $) and length of service (x, measured in months) for 30 employees. She estimates the model: Salary = Bo + B1 Service + ε. The following ANOVA table below shows a portion of the regression results. df SS M S F Regression 555,420 555,420 7.64 Residual 27 1,962,873 72,699 Total 28 2 ,518,293 Coefficients Standard Error t-stat p-value Intercept 784.92 322.25 2.44 0.02...
A financial analyst is examining the relationship between stock prices and earnings per share. She chooses fifteen, publicly traded companies at random and records for each the company's current stock price and the company's earnings per share reported for the past 12 months. Her data are given below, with X denoting the earnings per share from the previous year and y denoting the current stock price (both in dollars). A scatter plot of her data is shown in Figure 1....
13)-19) A company analyst is interested in the relationship between number of cars sold per month (in 1,000s) and three independent variables: price per gallon of gasoline (X1=Gas, in $), the prevailing interest rate for car loans (x2=Interest, in %), and the car model (x3=model, with X3=1, the car is standard; and X3=0, if the car is luxury). He took a sample of 50 observations and obtained the following output: Coefficients Standard Errort Stat P-value Intercept 96.0744 10.0080 5.60 0.0001...
I need help with - (d) Based on your results to parts (b) and (c), would you recommend using the least-squares regression line to predict the stock return of a company based on the CEO's compensation? Why? What would be a good estimate of the stock return based on the data in the table? - the final part of the problem. Thank you! The accompanying data represent the total compensation for 12 randomly selected chief executive officers (CEOs) and the...