A classic example of how fallacious statistical thinking can creep in. It is the 1960s, and you are trying to replicate some findings and support the hypothesis that smoking and cancer are related. From the local region you take a sample of 100 people and ask each whether they have cancer and whether they are smokers are not. The data are as follows. At alpha .05, is the occurence of cancer equal among smokers and non- smokers? Cancer No Cancer Smoker 15 15 Non-Smoker 15

A classic example of how fallacious statistical thinking can creep in. It is the 1960s, and you are trying to replicate some findings and support the hypothesis that smoking and cancer are related. From the local region you take a sample of 100 people and ask each whether they have cancer and whether they are smokers are not. The data are as follows. At alpha .05, is the occurence of cancer equal among smokers and non- smokers? Cancer No Cancer Smoker 15 15 Non-Smoker 15

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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You are a researcher interested in crime and crime rates. You’ve collected a sample of data from the county level for your state. You hypothesize that the rate of violent crimes will be higher in counties with bigger populations. Based on the below Pearson correlation results, is your hypothesis supported or rejected?
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Which of the following statements is not true? There is only one median for each variable. One definition of the median states that, for an odd number of observations, the median is the middle score when scores are placed in order of magnitude. Another term for the median is 50th percentile. The median is generally more sensitive to (i.e., affected by) the presence of a few extreme observations than is the mean.
A federal regulatory agency is investigating an advertised claim that a certain device can increase the gasoline mileage of cars (mpg). Ten such devices are purchased and installed in cars belonging to the agency. Gasoline mileage for each of the cars is recorded both before and after installation. The data are recorded here. Car 1 2 3 4 5 6 7 8 9 10 n x s Before (mpg) 19.1 29.9 17.6 20.2 23.5 26.8 21.7 25.7 19.5 28.2 10 23.22 4.25 After (mpg) 25.8 23.7 28.7 25.4 32.8 19.2 29.6 22.3 25.7 20.1 10 25.33 4.25 Change (mpg) 6.7 −6.2 11.1 5.2 9.3 −7.6 7.9 −3.4 6.2 −8.1 10 2.11 7.54 (a) The cars in the study appear to have grossly different mileages before the devices were installed. Use the change data to test whether there has been a significant gain in mileage after the devices were installed. Use ? = .05. H0: ?after ?before Ha: ?after ?before t = p-value
The scatterplot below shows the relationship between two random variables X and Y. (a) Is the correlation a good metric for describing the relationship between X and Y for these data? Why or why not? Regardless of your answer suppose you calculated the sample correlation between X and Y and found that r = -0.15. Explain in one sentence what this means. (b) If, as noted in (a), r = -0.15 then what is the value of the correlation between 2X and 5Y? (c) Based on (b) draw your best approximation to the least squares regression line that fits the data above. Also, make a rough sketch of the corresponding residual plot.
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