What is the significance of R and R2 and of a regression model?

Solution-: What is the significance of R and R2 and of a regression model?

Answered: What is the significance of R and R2…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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What are some examples of ways in which linear regression to create a beneficial statistical outcome, in a business setting?
What trade-off do you make including additional variables in your regression?
Show the difference between the "complete model" and "reduced model of regression analysis?
Suppose you a manager for a local car dealership, and you want to use a linear regression model to predict the price of a used car. You decide to use four predictor variables - "Age' (how long the car has been in use since it was produced), "Dents" (the number of visible dents on the outside of the car), "Accidents" (the number of accidents the car has been in), and "mpg" (the fuel efficiency of the car, measured in miles per gallon). Your dataset contains this information for the past 120 cars sold at your dealership. Using this model, your analysis finds an R² of 37%. What is the F statistic of your analysis? Note: 1- Only round your final answer. Round your final answer to two decimal places.
How do we assess the statistical fitness of the regression model?
6. another retail merchant who sells face masks spent a total $55 for advertising its product. using the regression model in (4), predict the sale of this merchant.
How to write the model specifications of a multiple regression analysis with dummy variables that are more than two categories? Provide your solutions using the example, y=spending,x1=education level (1 if primary,2 if secondary,3 if tertiary,4 if above),x2=type of job(1 if full times,2 if part timed,3 if retired) Write the regression equation of the example.
Describe a hypothetical study for which multiple regression with more than two predictor variables would be an appropriate analysis. Your description should include one dependent variable and three or more predictors.
What are the assumptions of a multiple linear regression model? What would you do to look for violations of the multiple linear regression model assumptions
Explain the curvilinear regression analysis?
Why is it necessary that the variables are significantly correlated before performing regression analysis?
When is the coefficient of certainty obtained from the regression equation equal to the square of the coefficient of correlation between the variables?

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