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Get Full Access to Elementary Statistics - 12 Edition - Chapter 10-2 - Problem 13
Get Full Access to Elementary Statistics - 12 Edition - Chapter 10-2 - Problem 13

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# Full answer: Testing for a Linear Correlation. In Exercises 1328, construct a

ISBN: 9780321836960 18

## Solution for problem 13 Chapter 10-2

Elementary Statistics | 12th Edition

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Problem 13

Testing for a Linear Correlation. In Exercises 1328, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the Pvalue or the critical values of r from Table A6 using = 0.05 . Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 103 exercises.)Lemons and Car Crashes Listed below are annual data for various years. The data are weights (metric tons) of lemons imported from Mexico andU.S. car crash fatality rates per 100,000 population [based on data from The Trouble with QSAR (or How I Learned to Stop Worrying and EmbraceFallacy) by Stephen Johnson, Journal of Chemical Information and Modeling, Vol. 48, No. 1]. Is there sufficient evidence to conclude that there is alinear correlation between weights of lemon imports from Mexico and U.S. car fatality rates? Do the results suggest that imported lemons cause carfatalities?Lemon Imports 230 265 358 480 530Crash Fatality Rate 15.9 15.7 15.4 15.3 14.9

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Groups Randomize control group Split individuals into two groups separately Control vs. treatment Compare the two averages correlation between the groups (Measure the strength before and after to get the experiment) Matching Observed and match into pairs with two treatments (Longitudinal and measures) Each group has their own control group within Find the change between the strength and average added between both old and new Compute: d= x1­x2 X1= response from one event X2= response from another event Analyzing D is what the gain and strength is Next: one variable to look over Find dbar and Sd After: use dbar and Sd to inference about Mud (Standard deviation of differences) To what value should we compare dbar Ho: Mud= 0 does

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