Question

1 Miles Price 2 87,719 $16,999 3 89,000 $7,995 4 94,148 $10,395 5 108,772$6,999 6 126,645 $6,900 7 139,858 $7,450 8 150,672 $7,950 9 154,381 $7,495 10 179,621 $5,999 11 313,397 $2,800

Question: You are now ready to construct your own test and collect your own data. For this lab you will be ...

You are now ready to construct your own test and collect your own data. For this lab you will be answering the question: How does use car mileage affect its predicted asking price?

1. 1st clearly state the population for this test:

2. Clearly state the variables being examined:

3. Would you expect a positive or negative correlation between mileage and price?

Non-zero Neutral Positive or Negative

4. Explain the processor you are going to use to collect data. You will need a sample size of at least 20. You may use technology and websites such as craigslist.com to collect your data.

5. Report your data below presented in a table

6. Now run a LinRegTTest and present your linear model stated in the form y = a +bx :

7.State your slope and explain how your slope would affect the projected price of the car:

8. Now state your correlation. Explain whether you would consider this a strong or weak correlation:

9. Explain some of the confounding variables that go into setting the price of a used car outside of mileage.

10. Can we conclude from our study that mileage causes the price of a used car to go down? Why or why not?

Answer 1

All the parts of this question is answered below:

(1) Population is the the total number of cars in that locality where the experiment is conducted...

(2) Variables are the Miles and the price of the respective cars...

Part 3 to 10:

Miles 87719 89000 94148 108772 126645 139858 150672 154381 179621 313397 Price 16999 7995 10395 6999 6900 7450 7950 7495 5999 2800 9 3 9 9 5

SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.692712021 0.479849945 0.414831188 51221.34918 10 ANOVA df MS F Significance F Regression Residual Total 1 19362829199 1.94E+10 7.380177 0.026385213 820989012897 2.62E+09 40351842096 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept Price 247102.699 41121.56121 6.009079 0.00032 152276.2088 341929.1892 152276.209 341929.1892 12.6795336 4.667344796-2.71665 0.026385-23.442451.9166172-23.44245 1.916617196

Here, the value of correlation coefficient is -0.69... This means that the relationship is strong and negative...

The Mathematical equation/Regression Equation is: Miles = 247102.7 - 12.68*Price

Here, slope for price is negative, so if the price increases, the miles factor decreases...

End of the Solution...