Presented by: Alex Kelson, Ben Sparks, Drew Walsh, Oyebola Akinmulero, Shaghayegh Tareh, Tim Pearson, Tina Tran 1

Table of Contents 1. Find a statistical question to answer Located on Page 3 2. Come up with your own hypothesis Located on Page 3 3. Collect data Raw Data Located on Page 4 (Table 1 and Graph 1) 4. Organize and summarize the data Located on Pages Plot x vs. y and calculate linear correlation coefficient, r Located on Page 7 6. Predicted Y Located on page 8 Residual Located on page 9 7. Check to see if the linear model assumption is valid Located on Page Make a few predictions Located on Page Afterthought Located on Page 12 Sources located on page 13 2

Statistical Analysis Is there a correlation between the miles on a used Toyota Corolla LE and the asking price at a used car dealership? We believe that there is a linear correlation where more miles that a used Toyota Corolla LE has the lower the sticker or asking price will be at the used car dealership. 3

Data on Toyota Corolla LE Mileage (X)Price (Y) $18, $17, $17, $16, $15, $15, $15, $15, $15, $14, $14, $14, $14, $14, $14, $13, $13, $13, $13, $12, $12, $11, $10, $10, $10, $10, $10, $ $ $ Table 1Graph 1

Dataset X (mileage) ColumnnMeanVarianceStd. Dev.Std. Err.MedianRangeMinMaxQ1Q3 MILEAGE E

Dataset Y (Price) ColumnNMeanVarianceStd. Dev.Std. Err.MedianRangeMinMaxQ1Q3 PRICE

Best Fit Line and Correlation Coefficient Y= x R= MILES PRICEPRICE 7

Calculations and Graph for Predicted Y Predicted Y vs X To get predicted Y we plug Observed X from Table 2 into the Best Fit Line Equation of Y= x (Graph 3) 8 Table 2

Calculations and Graph for Residual Observed XObserved YPredicted YResidual Residual vs. X PRICEPRICE MILES 9 Graph 4 Table 2 Residual To produce the residual we subtract the Observed Y from the Predicted Y in Table 2. This produces Graph 4.

Linear Model Assumption Due to the fact that there is a linear correlation using the best fit line model we have met the criteria for section A on #7 Since there was no discernible pattern in the graph of “Residual vs X” (found on Page 8), the data is linearly related. Since we have used 30 points in our data set and our correlation coefficient or R =.8615 this is much higher than the required.361 we have found a strong positive correlation. We have concluded that using the data from cars.com, a strong correlation between the miles on a used vehicle will lower the sticker/asking price of a Toyota Corolla LE. 10

Predictions Using Equation To get predictions we come up with X that is within the ranges of our data and plug it into the Best Fit Line Equation of Y= x XY Predicted using Equation 11 Graph 5 Table 3

After Thought Did you just do a convenience or voluntary-response sampling to collect your data? The sampling data was convenience based. We found it through an internet search. Did your study suffer from too few data points? We don’t believe the study suffered from too few data points, it points out clearly that car value decreases with increased mileage. Are you misrepresenting the data? No we are not misrepresenting the data. Is your analysis correct? The analysis is correct. Does your conclusion make sense? Yes our conclusion makes sense. We believe that the study was useful for our reader. However, most of this knowledge is considered common sense. We think it would have been helpful to research a variety of cars and compare resale value based on mileage. This study could have more value by comparing upgrades vs. stock resale value and this could be done for multiple makes and models. This could influence the reader’s decision between makes and models and the upgrades purchased depending on the added resale value. 12

Sources All statistical data was acquired using the Cars.com search engine for “Used Toyota Corolla LE” search grid within 10 miles of accessed on 11/14/11 ma9Zfi0Zg3hZinqZm5d?sf1Dir=DESC&mkId=20088&mdId=20861&rd=10&zc=84070&PMmt=1-1- 0&stkTypId=28881&sf2Dir=ASC&sf1Nm=price&sf2Nm=miles&rpp=50&feedSegId=28705&searchSource =GN_REFINEMENT&crSrtFlds=stkTypId-feedSegId-mkId-mdId-trId&pgId=2102&trId=