Question

Does the correlation among the independent variables post a problem in a multiple linear regression model?...

Does the correlation among the independent variables post a problem in a multiple linear regression model? Explain

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

Yes, correlation among the independent variables is a big issue in multiple linear regression model.

One of the main problem related to the correlation among the independent variable in multiple linear regression is that one of the important predictor(independent variable) become insignificant due to correlation with other predictors. Due to this problem, correlation coefficient value gets reduced or sometimes its value gets reversed, i.e. it become negative from positive and sometimes becomes positive from negative correlation.

Addition and removal of predictor variables create major issue in the regression analysis because adding or removing one variable shows significant change in other variable's values.

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
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
__________ refers to the degree of correlation among independent variables in a regression model. a. Multicollinearity...
__________ refers to the degree of correlation among independent variables in a regression model. a. Multicollinearity b. Confidence level c. Rank d. Tolerance __________ is used to test the hypothesis that the values of the regression parameters ß1, ß2, ...ßq are all zero. a. Extrapolation b. A t test c. An F test d. The least squares method What would be the coefficient of determination if the total sum of squares (SST) is 23.29 and the sum of squares due...
Regression analysis involves lurking variables, outliers, scatterplots, linear correlation coefficient, and regression equation. Answer the following...
Regression analysis involves lurking variables, outliers, scatterplots, linear correlation coefficient, and regression equation. Answer the following 2 questions for your main post: How have you used data to showcase an example or solve a problem? Did you get the outcome you expected? Explain.
What socio-economic variables could serve as Independent variables when conducting a multiple linear Regression with the...
What socio-economic variables could serve as Independent variables when conducting a multiple linear Regression with the dependent variable "Happiness Index"? (I already have GDP/capita, divorce rate, unemployment rate, urbanization rate) Maybe you also can come up with an "interesting" one where there is not yet so much Research on a potential correlation with Happiness. Thanks in advance
In a simple linear regression model, if the independent and dependent variables are negatively linearly related,...
In a simple linear regression model, if the independent and dependent variables are negatively linearly related, then the standard error of the estimate will also be negative.
Complete the following ANOVA table for a multiple linear regression model and answer the following questions....
Complete the following ANOVA table for a multiple linear regression model and answer the following questions. Source df SS MS F Regression 93 30 Total 33 267 a) How many independent variables are included in the model? b) State the null and alternate hypothesis to be tested. c) At a 0.01 level of significance, is the multiple linear regression model significant? (Justify) d) How many data points have been collected?
Complete the following ANOVA table for a multiple linear regression model and answer the following questions....
Complete the following ANOVA table for a multiple linear regression model and answer the following questions. Source df SS MS F Regression 93 30 Total 33 267 a) How many independent variables are included in the model? b) State the null and alternate hypothesis to be tested. c) At a 0.01 level of significance, is the multiple linear regression model significant? (Justify) d) How many data points have been collected?
With a multi-variable linear regression model how can we decide which independent variables to remove from...
With a multi-variable linear regression model how can we decide which independent variables to remove from the model?
Multiple Linear Regression We consider the misspecification problem in multiple linear regression. Suppose that the following...
Multiple Linear Regression We consider the misspecification problem in multiple linear regression. Suppose that the following model is adopted y = X1β1 + ε while the true model is y = X1β1 + X2β2 + ε. For both models, we assume E(ε) = 0 and V (ε) = σ^2I. Figure out conditions under which the least squares estimate we obtained is unbiased.
1. Consider an actual proof problem 2. The problem should estimate one multiple linear regression, or...
1. Consider an actual proof problem 2. The problem should estimate one multiple linear regression, or a logistic regression. Explain the estimation. 3. Consider a different model from step 2. You can try adding other random variables to explain your model, or consider different ways to explain (For example: probit model, lasso, trees, random forest, gradient boosting, or neural net). Then, compare the estimation results of the original model and the new model. ps. If you answer the question with...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT