Question

Which of the following r values would be the most useful for using with regression? Question...

Which of the following r values would be the most useful for using with regression?

Question 3 options:

r=0

r=.3

r=.05

r= -.06

Homework Answers

Answer #1

R-value is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination, or the coefficient of multiple determination for multiple regression.

The definition of R-value is fairly straight-forward; it is the percentage of the response variable variation that is explained by a linear model. Or:

R-value = Explained variation / Total variation

R-value is always between 0 and 100% or 0 to 1:

  • 0% or 0 indicates that the model explains none of the variability of the response data around its mean.
  • 100% or 1 indicates that the model explains all the variability of the response data around its mean.

In general, the higher the R-value, the better the model fits your data.

So, it is clear that R-value never be negative.

So, here in this question 0.3 R-value is most useful.

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
When is linear regression of no value? Question 32 options: 1) r > 0 2) r...
When is linear regression of no value? Question 32 options: 1) r > 0 2) r = 1 3) r = 4) r = 0 5) r < 0
The regression effect is best described as Question 4 options: A) A condition in which the...
The regression effect is best described as Question 4 options: A) A condition in which the predicted Y values will be closer to the mean for Y, than the X values will be to the mean for X. B) A condition in which the X values will be closer to the mean for X, than the Y values will be to the mean for Y. C) A study originally done by Galton which found sons on average are taller than...
Using R and the data in the table below, perform the regression of D on C...
Using R and the data in the table below, perform the regression of D on C (i.e., report the regression equation). Hint: The code to enter the vectors C and D into R is: C <- c(3, 6, 8, 9, 1, 3) D <- c(2, 7, 5, 4, 0, 4) C D 3 2 6 7 8 5 9 4 1 0 3 4 You must figure out how to obtain the regression equation from R. Enter the code below...
1. Compute the regression equation (regression coefficient and constant) using the same data from the previous...
1. Compute the regression equation (regression coefficient and constant) using the same data from the previous question. Compute the explained variance (R Square) and the standardized regression coefficient (beta) for this model. For R Square, Sums of Squares Explained = 235.944; Sums of Squares Total = 520. 2. Given: sample R Square 0.232; SS explained = 2848.62; SS residual = 9425.25; N = 62. Test the hypotheses Ho: R square = 0; Ha: R square NE 0 at the .05...
Using the attached regression output, answer the following: SUMMARY OUTPUT Regression Statistics Multiple R 0.972971 R...
Using the attached regression output, answer the following: SUMMARY OUTPUT Regression Statistics Multiple R 0.972971 R Square 0.946673 Adjusted R Square 0.944355 Standard Error 76.07265 Observations 49 ANOVA df SS MS F Significance F Regression 2 4725757 2362878 408.3046 5.24E-30 Residual 46 266204.2 5787.049 Total 48 4991961 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -0.46627 14.97924 -0.03113 0.975302 -30.6179 29.68537 X1 0.09548 0.084947 1.123997 0.266846 -0.07551 0.26647 X2 0.896042 0.205319 4.364141 7.16E-05 0.482756 1.309328 a. What...
QUESTION 19       Polynomial regression was used to predict sales (Y) using advertising expenditure (X) and...
QUESTION 19       Polynomial regression was used to predict sales (Y) using advertising expenditure (X) and its square (X2) as independent variables. The following information is available: Predictor Coefficients Standard Error Constant 328.42 29.42 X 10.970 1.832 X2 -.12507 .02586 ANOVA Source DF SS F Regression 42.56 Residual Total 11 14,107.7 Testing, at the .05 level of significance, if the quadratic term is useful for the prediction of sales, the alternative hypothesis is: a. Ha:  b1 ¹ 0 b. Ha:  b2 =...
Which of the following ratios would be least useful in determining a company's ability to pay...
Which of the following ratios would be least useful in determining a company's ability to pay its expenses and liabilities? Question 45 options: Current ratio Acid-test ratio Price-earnings ratio Times interest earned ratio
Question 1 Which statement is false about what Data Types defines Question 1 options: What values...
Question 1 Which statement is false about what Data Types defines Question 1 options: What values a variable cannot hold? How much memory will be reserved for the variable? What value a variable will hold? How the program will use the data type? Question 2 Using the structure below, which of the following statements about creating an array (size 20) of structures are not true? struct Employee{     string emp_id;     string emp_name;     string emp_sex; }; Question 2 options:...
Which of the following scenarios would most likely increase financial leverage? Question 3 A company issues...
Which of the following scenarios would most likely increase financial leverage? Question 3 A company issues bonds to purchase treasury stock. A company buys fixed assets with cash. A company signs an operating lease agreement for a new manufacturing facility. A company increases its dividend payout, making it in cash on the following payment date. Question 4: Bolton Company substantially increased its allowance for bad debt. Which of the following effects will occur? Question 4 options: It will reduce the...
Which inventory model would be the most useful for perishable goods in a grocery chain? Why?...
Which inventory model would be the most useful for perishable goods in a grocery chain? Why? Which would be the most appropriate for gasoline at a service station?