Details: Complete the following exercises located at the end of each chapter and put them into a Word document to be submitted as directed by the instructor. Show all relevant work; use the equation editor in Microsoft Word when necessary.
Details:
Complete the following exercises located at the end of each chapter and put them into a Word document to be submitted as directed by the instructor.
Show all relevant work; use the equation editor in Microsoft Word when necessary.
X Y
64 66
40 79
30 98
71 65
55 76
31 83
61 68
42 80
57 72
(b) Construct a scatterplot for X and Y . Verify that the scatterplot does not describe a pronounced curvilinear trend. (c) Calculate r using the computation formula (6.1). 6.8 Calculate the value of r using the computational formula (6.1) for the following data:
X Y
2 8
4 6
5 2
3 3
1 4
7 1
2 4
*6.10 On the basis of an extensive survey, the California Department of Education reported an r of 2 .32 for the relationship between the amount of time spent watching TV and the achievement test scores of schoolchildren. Each of the following statements represents a possible interpretation of this finding. Indicate whether each is true or false.
(a) Every child who watches a lot of TV will perform poorly on the achievement tests.
(b) Extensive TV viewing causes a decline in test scores.
(c) Children who watch little TV will tend to perform well on the tests.
(d) Children who perform well on the tests will tend to watch little TV.
(e) If Gretchen’s TV-viewing time is reduced by one-half, we can expect a substantial improvement in her test scores.
(f) TV viewing could not possibly cause a decline in test scores.
6.11 Assume that an r of .80 describes the relationship between daily food intake, measured in ounces, and body weight, measured in pounds, for a group of adults. Would a shift in the units of measurement from ounces to grams and from pounds to kilograms change the value of r ? Justify your answer.
7.8 Each of the following pairs represents the number of licensed drivers ( X ) and the number of cars ( Y ) for seven houses in my neighborhood:
Drivers(x) Cars(Y)
5 4
5 3
2 2
2 2
3 2
1 1
2 2
(a) Construct a scatterplot to verify a lack of pronounced curvilinearity.
(b) Determine the least squares equation for these data. (Remember, you will first have to calculate r , SS y , and SS x .)
(c) Determine the standard error of estimate, s y | x , given that n 5 7.
(d) Predict the number of cars for each of two new families with two and five drivers.
7.10 Assume that r 2 equals .50 for the relationship between height and weight for adults. Indicate whether the following statements are true or false.
(a) Fifty percent of the variability in heights can be explained by variability in weights.
(b) There is a cause-effect relationship between height and weight.
(c) The heights of 50 percent of adults can be predicted exactly from their weights.
(d) Fifty percent of the variability in weights is predictable from heights.
7.13 In the original study of regression toward the mean, Sir Francis Galton noted a tendency for offspring of both tall and short parents to drift toward the mean height for offspring and referred to this tendency as “regression toward mediocrity.” What is wrong with the conclusion that eventually all heights will be close to their mean?
