B. Write a linear equation from graph info predicting price from miles. C. Does

Question

B. Write a linear equation from graph info predicting price from miles.
C. Does the intercept have a meaningful interpretation. If yes provide one within context of this problem
D. What is the percent of variability in Price is accounted for by this linear model. simple linear regression results: Dependent Variable: Price (in pounds) Independent Variable: Miles (in Thousands) Price (in pounds) = 19301.992-209.38023 Miles (in Thousands) Sample size: 54 R (correlation coefficient) =-0.48189278 R-sq = 0.23222065 Estimate of error standard deviation: 4553.9103 Parameter estimates: Parameter Estimate Std. Err. AlternativeDF T-Stat P-value Intercept 19301.9921235.3191 Slope-209.3802352.796093 0 52 15.625 106

Explanation / Answer

Given that,

dependent variable is price

independent variable is miles.

Regressino equation is,

Price = 19301.992 - 209.38023*miles

Here intercept = 19301.992

Slope = 209.38023

Intercept of slope : For one unit change in miles will be 209.38023 unit decrease in price.

Here negative sign of slope indicates that there is negative realtionship between price and slope.

R-sq = 0.2322

Interpretation of R-sq : It expresses the proprotion of variation in price whiich is explained by variation in miles.

Also we can test the hypothesis that,

H0 : B = 0 Vs H1 : B not= 0

where B is population slope for miles.

Assume alpha = level of significance = 0.05

Here test statistic follows t-distribution. This test is also known as test for individual slope.

Test statistic = -.3.9658

P-value = 0.0002

P-value < alpha

Reject H0 at 0.05 level of significance.

COnclusion : The population slope for miles is differ than 0.

We get significant result about miles.

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