Dr. Thomas R. Boucher Texas A&M University-Commerce
Name:
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The file ‘2013 Car MPG.csv’ contains EPA MPG estimates for a variety of 2013 models. We would like to compare the number of cylinders ‘cylinders’ across the various classes (‘class’) of automobiles. Consider the automobiles used in the testing to be a representative sample of all 2013 automobiles.
(1)
Use StatCrunch to create a contingency table with ‘class’ defining the rows and
‘cylinders’ defining the columns. Paste the table here. Does the table suggest anything?
 There are several 0’s or empyy cells which will impact the chi values, most of which come from pickup and suv
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It appears that most cars across class have either 4, 6, or 8 cylinders.
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Few cars across class have 5 or 12 cyllinders.
(2) Use StatCrunch to create individual bar charts for ‘class’ and for ‘cylinders’, and a grouped bar chart for the data for ‘class’ and ‘cylinders’. Include the plots here.
Do the plots show anything?

Dr. Thomas R. Boucher Texas A&M University-Commerce

The highest frequency of cylinders are 4,6, and 8
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The highest frequency of car classes are compact, and midsize
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We can see overlap between the cars with the highest frequency and the highest cylinder frequency
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4 cylinder mostly has compact and midsize
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6 cylinders is the most varied
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8 cylinders is most SUV and pickup
(3)
Use Pearson’s Chi-Square test in StatCrunch to test for an association between
‘class’ and ‘cylinders’. Paste the output here. What do you conclude? Can you be confident in the results?

This chi square value is very large

Dr. Thomas R. Boucher Texas A&M University-Commerce

The p value is very small and we reject the null and accept the alternative because of this
 We can’t be confident in the result because over 20% of cells have a count less than 5
(4) You should have seen a significant association (with caveats) between ‘class’ and
‘cylinders’. Use StatCrunch to create another contingency table containing the observed and expected counts, and the contributions to the Chi-Square and use these to interpret the association.
 The biggest reasons we rejected the null are compact cars with 4 cylinders, SUV’s with 4 cylinders, and Suvs with 8 cylinders.
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AS we can see there are several values that are more than expected such as 8 cylinder and compact cars
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There are more however that are less than expected such as 4 cylinder compact cars.
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We can see that those that were less than expected were big contributions which is likely why we got the results we did.