Question

Which of the following is TRUE in simple linear regression? A. A residual represents the difference...

Which of the following is TRUE in simple linear regression?

A.

A residual represents the difference between an observed Y value and predicted X value for a given Y value.
B.

A residual is always greater than the observed Y value.
C.

A residual represent the difference between the average X value and the average Y value.
D.

None of the above.
Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #2

ANSWER:

Which of the following is TRUE in simple linear regression:

We have to obtained the given statements is true in simple regression equation is

Here,

Residual formula is  

Residual =[ y -( y bar) ] .

Therefore ,

  • A residual represents the difference between an observed Y value and predicted X value for given Y value.

OPTION (A) is TRUE in simple regression .

NOTE:: I HOPE YOUR HAPPY WITH MY ANSWER....***PLEASE SUPPORT ME WITH YOUR RATING...

***PLEASE GIVE ME "LIKE"...ITS VERY IMPORTANT FOR ME NOW....PLEASE SUPPORT ME ....THANK YOU

answered by: anonymous
0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
In the simple linear regression model estimate Y = b0 + b1X A. Y - estimated...
In the simple linear regression model estimate Y = b0 + b1X A. Y - estimated average predicted value, X – predictor, Y-intercept (b1), slope (b0) B. Y - estimated average predicted value, X – predictor, Y-intercept (b0), slope (b1) C. X - estimated average predicted value, Y – predictor, Y-intercept (b1), slope (b0) D. X - estimated average predicted value, Y – predictor, Y-intercept (b0), slope (b1) The slope (b1) represents A. the estimated average change in Y per...
Which of the following are true in simple linear regression? True or False for each There...
Which of the following are true in simple linear regression? True or False for each There is only one independent variable (X). Y is the dependent variable. The relationship between X and Y is described by a linear function. Changes in Y are assumed to be related to changes in X. X is the independent variable because Y is dependent on X
In simple linear regression, the method of least squares determines the line that minimizes the sum...
In simple linear regression, the method of least squares determines the line that minimizes the sum of squared deviations between the observed y values and: a. the average of the y values b. the average of the x values c. the fitted line d. the line of residual errors
13. Interpreting the intercept in a simple linear regression model is: * (A) reasonable if the...
13. Interpreting the intercept in a simple linear regression model is: * (A) reasonable if the sample contains values of x around the origin. (B) not reasonable because researchers are interested in the effect of a change in x on the change in y. (C) reasonable if the intercept’s p-value is less than 0.05. (D) not reasonable because it is always meaningless. 14. Which of the following is NOT one of the assumptions necessary for simple linear regressions?: * (A)...
Correlation and Regression True or False 3 Questions: K). In simple linear regression predicting Y from...
Correlation and Regression True or False 3 Questions: K). In simple linear regression predicting Y from X, the unstandardized coefficient of the X variable will always equal the Pearson r between X and Y. (Assume X and Y are not measured as z scores). L). In simple linear regression predicting Y from X, the standardized coefficient of the X variable will always equal the Pearson r between X and Y. M). In multiple regression predicting Y from X, the standardized...
Explain the difference between simple and multiple linear regression. A. Simple linear regression is faster B....
Explain the difference between simple and multiple linear regression. A. Simple linear regression is faster B. The difference is in how many independent variables used in the regression model C. There is no difference D. There is a difference in the linearity
Which of the following values is NOT a valid (or possible) correlation coefficient? A. 0.7923 B....
Which of the following values is NOT a valid (or possible) correlation coefficient? A. 0.7923 B. 0.0001 C. 1.2301 D. -0.9239 In regression, the space between the regression line (line of best fit) and the actual data points is the ___________. A. Standard deviation. B. Error. C. Predicted value. D. Observed value. In regression, what does error indicate? A. The difference between the predicted value and the observed value Y for a given X. B. The difference between the predicted...
A residual is: The difference between a data point and the regression line. A value that...
A residual is: The difference between a data point and the regression line. A value that can be 1 or zero. A value that is always negative because it is a difference The difference between two different lines. The properties of r include: r is sensitive to very high quantities The value of r is not affected if the values of either variable are converted into a different scale You must define the independent and dependent variables All of the...
The main difference between simple linear regression and multiple regression is: Selected Answer: Multiple regression uses...
The main difference between simple linear regression and multiple regression is: Selected Answer: Multiple regression uses more than one explanatory variable, while simple linear regression only uses one. Answers: Multiple regression uses more than one response variable, while simple linear regression only uses one. Simple linear regression uses more than one response variable, while multiple regression only uses one. Multiple regression uses more than one explanatory variable, while simple linear regression only uses one. Simple linear regression uses more than...
1. You are given the following data to fit a simple linear regression x 1 2...
1. You are given the following data to fit a simple linear regression x 1 2 3 4 5 y -2 4 2 -1 0 Using linear least squares, determine the t-value for testing the hypothesis that no linear relationship exist between y and x. (a) 0.01, (b) 0.03, (c) 0.09, (d) 0.11, (e) 0.13
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT