Question

In: Statistics and Probability

How would you use multiple regression analysis to purchase a used car? List all the variables...

How would you use multiple regression analysis to purchase a used car? List all the variables you would use to and what type of analysis weights you would place on them?

Solutions

Expert Solution

There is no specific answer to this problem. Whatever we take we can always improvise it with multiple regression.

But we can create a rough model.

So you are going to buy a used car what factors will you consider Kilometers driven or Miles driven till date.

body condition , engine condition , servicing reports , price of other cars( similar models ), number of previous owners ,model make year etc.

we can have so many factors. but important is which will be the dependent variable ......what you are going to give for that car?? Money right! So it can be your dependent variable. You change other factors it will change the price.In theory this is how it should work.

weights will be your coefficients of these independent variables.

so for example if miles driven is more you will pay less right?

so it will have a negative coefficient and also a effective one means more weight to this factor as it is one of the crucial factors for used cars.

if you are using some rating for condition of car like 6/10 then this will have a positive relationship.

similarly you can have different weights according to variables.

Please upvote if you find this helpful


Related Solutions

How would you differentiate among multiple discriminant analysis, regression analysis, logistic regression analysis, and analysis of...
How would you differentiate among multiple discriminant analysis, regression analysis, logistic regression analysis, and analysis of variance and demonstrate statistical significance for each?
1. A multiple linear regression model should not be used if: A The variables are all...
1. A multiple linear regression model should not be used if: A The variables are all statistically significant. B The coefficient of determination R2 is large. C Both of the above. D Neither of the above. 2. Consider a multiple linear regression model where the output variable is a company's revenue for different months, and the purpose is to investigate how the revenue depends upon the company's advertising budget. The input variables can be time-lagged so that the first input...
11.30  A simpler model. In the multiple regression analysis using all four explanatory variables, Theaters and...
11.30  A simpler model. In the multiple regression analysis using all four explanatory variables, Theaters and Budget appear to be the least helpful (given that the other two explanatory variables are in the model). (a) Perform a new analysis using only the movie’s opening-weekend revenue and IMDb rating. Give the estimated regression equation for this analysis. (b) What percent of the variability in USRevenue is explained by this model? (c) Test the null hypothesis that Theaters and Budget combined add...
Describe how simple linear regression analysis and multiple regression are used to support areas of industry...
Describe how simple linear regression analysis and multiple regression are used to support areas of industry research, academic research, and scientific research.
List three variables, and how they are measured, for which you would use the mode as...
List three variables, and how they are measured, for which you would use the mode as the most appropriate measure of central tendency.
e. Multiple Regression. Identify at least 3 variables for which you could calculate a multiple regression....
e. Multiple Regression. Identify at least 3 variables for which you could calculate a multiple regression. Describe the variables and their scale of measurement. Which variables would you include as the predictor variables and which as the outcome variable? Why? Which regression method would you use and why? What would R2 and adjusted R2 tell you about the relationship between the variables?
According to Pollock and Edwards, a multiple regression analysis contains at least __ independent variables a....
According to Pollock and Edwards, a multiple regression analysis contains at least __ independent variables a. 0 b. 1 c. 2 d. none of the above According to Pollock and Edwards, the .05 threshold suggests that researchers wish to commit _____ less than five times out of 100 tests. a. individual fallacy b. Type I error c. Type II error d. ecological fallacy According to Pollock and Edwards, a p-value determines the exact probability of obtaining the observed sample difference...
Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars)...
Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X1 in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 0 =female and 1=male). The following is a partial result of a computer program that was used on a sample of 20 individuals. Coefficient    Standard Error              X1 0.6251 0.094              X2 0.9210 0.190              X3 -0.510 0.920 Analysis of Variance...
A student used multiple regression analysis to study how family spending (y) is influenced by income...
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. Anova df ss regression 3 45.9634 residual 11 2.6218 Total coefficient Standard error intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 Calculate the estimated regression equation for the relationship between the variables,coefficient of determination. What...
A student used multiple regression analysis to study how family spending (y) is influenced by income...
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additionsto savings(x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 a. Write out the estimated regression equation for the relationship between the variables. (1 mark) b....
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT