Question

When you calculate your regression line, you are: Minimizing the sum of the errors Finding the...

When you calculate your regression line, you are:

Minimizing the sum of the errors

Finding the absolute value of the error terms and minimizing the sum of the absolute values

Finding the error for each observation, squaring the error and minimizing the sum

Homework Answers

Answer #1

Answer:

When you calculate your regression line, you are: Finding the error for each observation, squaring the error and minimizing the sum

Explanation:

The regression is utilized  to understand the association between independent variable and dependent variable.

Here we utilize the regression  line for that , regression  line is the stright line linear  condition that can be utilized for prediction of values.this condition is discover utilizing the least square estimator.

Here least square is the strategy of squaring the error and minimizing the sum.

So we can compute the regression  line utilizing the least square technique.

Therefore When you calculate your regression line, you are: Finding the error for each observation, squaring the error and minimizing the sum.

Hence the "Option - 3"  is the correct answer.

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 finding the regression line, why would we minimize the squared error instead of the mean...
When finding the regression line, why would we minimize the squared error instead of the mean squared error? Would minimizing the root mean square have given us a different/better answer?
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
The regression line can never be used for prediction. True False The slope is the amount...
The regression line can never be used for prediction. True False The slope is the amount Y changes for every increase in X. True False "When you calculate a regression equation, you want the line with the most error. " True False "Correlation measures the linear relationship between two variables, while a regression analysis precisely defines this line. " True False The predicted value based on a regression equation is a perfect prediction. True False What represents the intercept (the...
Suppose we have used the ordinary least squares to estimate a regression line. Now, to calculate...
Suppose we have used the ordinary least squares to estimate a regression line. Now, to calculate the residual for the ith observation xi, we do not need one of the followings: Select one: A.the standard error of the estimated slope. B.the estimated slope. C.the estimated intercept. D.the actual value of yi.
Question 4. Construct a diagram of a scatterplot with a best-fitting regression line (i.e. one that...
Question 4. Construct a diagram of a scatterplot with a best-fitting regression line (i.e. one that is fitted by eye). Label your axes and indicate which axis is the dependent variable and which axis is the independent variable. In your diagram indicate a residual. Write out a simple linear regression model and describe what each part of the model is (for example what is ??) use the simplear regression formula as  ?i = ? + ??i + ?i •?i is the...
Select all the statements that are true of a least-squares regression line. 1. R2 measures how...
Select all the statements that are true of a least-squares regression line. 1. R2 measures how much of the variation in Y is explained by X in the estimated linear regression. 2.The regression line maximizes the residuals between the observed values and the predicted values. 3.The slope of the regression line is resistant to outliers. 4.The sum of the squares of the residuals is the smallest sum possible. 5.In the equation of the least-squares regression line, Y^ is a predicted...
In your own words, describe potential errors that could ensue when performing multiple regression, in addition...
In your own words, describe potential errors that could ensue when performing multiple regression, in addition describe ways to prevent such errors.
Which is not correct regarding the estimated slope of the OLS regression line? a. It shows...
Which is not correct regarding the estimated slope of the OLS regression line? a. It shows the change in Y for a unit change in X. b. It is divided by its standard error to obtain its t statistic. c. It may be regarded as zero if its p-value is less than α. d. It is chosen so as to minimize the sum of squared errors.
Computing the regression line and making predictions Suppose you are a dolphin trainer at SeaWorld. You...
Computing the regression line and making predictions Suppose you are a dolphin trainer at SeaWorld. You teach the dolphins by rewarding them with fish treats after each successful attempt at a new trick. The following table lists the dolphins, the number of treats per success given to each, and the average number of attempts necessary for each to learn to perform the tricks. Dolphin Number of Treats Number of Attempts Diana 3 7 Frederick 2 8 Fatima 4 5 Marlin...
1. Consider the following regression line: i= -7.29 + 1.93 x YearsEducation. You are told that...
1. Consider the following regression line: i= -7.29 + 1.93 x YearsEducation. You are told that the t-ratio on the slope coefficient was 24.125. What is the standard error of the slope coefficient? A. 0.30 B. -0.08 C. 0.08 D. 1.64 2. In the simple linear regression model Yi = β0 + β1Xi + ui:   A. the absolute value of the slope is typically between 0 and 1. B. the intercept is typically small and unimportant. C. β0 + β1Xi...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT