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Ch. 10 - Correlation and Regression
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446Not the one you use?Change textbook
Chapter 10, Problem 10.CQQ.6

Exercises 1–10 are based on the following sample data consisting of costs of dinner (dollars) and the amounts of tips (dollars) left by diners. The data were collected by students of the author.
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Change in Scale Exercise 1 stated that for the given paired data, r = 0.846. How does that value change if all of the amounts of dinners are left unchanged but all of the tips are expressed in cents instead of dollars?

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1
Understand the problem: We are given a correlation coefficient (r = 0.846) for paired data of dinner costs and tips in dollars. We need to determine how this correlation changes if tips are converted from dollars to cents.
Recall the property of correlation: The correlation coefficient (r) is a measure of the strength and direction of a linear relationship between two variables. It is unitless and invariant to changes in scale or units of measurement.
Consider the effect of changing units: Converting tips from dollars to cents is a linear transformation (multiplying by 100). Such transformations do not affect the correlation coefficient because correlation is based on standardized values (z-scores) which are unaffected by changes in scale.
Conclude the effect on correlation: Since correlation is unaffected by linear transformations of the data, the correlation coefficient remains the same even if tips are expressed in cents instead of dollars.
Summarize the result: The value of the correlation coefficient (r = 0.846) does not change when the tips are converted from dollars to cents.

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Correlation Coefficient (r)

The correlation coefficient, denoted as 'r', measures the strength and direction of a linear relationship between two variables. It ranges from -1 to 1, where values close to 1 or -1 indicate a strong linear relationship, and values near 0 suggest a weak linear relationship. In this context, r = 0.846 suggests a strong positive correlation between dinner costs and tips.
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Scale Invariance of Correlation

Correlation is a scale-invariant measure, meaning it is unaffected by changes in the scale of measurement of the variables. This implies that multiplying all values of one variable by a constant (such as converting dollars to cents) does not change the correlation coefficient. Therefore, expressing tips in cents instead of dollars will not alter the value of r.
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Linear Transformation

A linear transformation involves changing a variable by multiplying it by a constant and/or adding a constant. In this problem, converting tips from dollars to cents is a linear transformation (multiplying by 100). Such transformations do not affect the correlation coefficient, as correlation measures the relative, not absolute, changes between variables.
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Related Practice
Textbook Question

Exercises 1–10 are based on the following sample data consisting of costs of dinner (dollars) and the amounts of tips (dollars) left by diners. The data were collected by students of the author.

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Scatterplot Construct a scatterplot and comment on the pattern of points.

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Textbook Question

Interpreting a Computer Display

In Exercises 5–8, we want to consider the correlation between heights of fathers and mothers and the heights of their sons. Refer to the StatCrunch display and answer the given questions or identify the indicated items. The display is based on Data Set 10 “Family Heights” in Appendix B. (The response y variable represents heights of sons.)

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Height of Son Should the multiple regression equation be used for predicting the height of a son based on the height of his father and mother? Why or why not?

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Textbook Question

Exercises 1–10 are based on the following sample data consisting of costs of dinner (dollars) and the amounts of tips (dollars) left by diners. The data were collected by students of the author.

Predictions The sample data result in a linear correlation coefficient of r = 0.846 and the regression equation y^ = -0.00777 + 0.145x. What is the best predicted amount of tip, given that the cost of dinner was \$84.62? How was the predicted value found?

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Textbook Question

Notation The author conducted an experiment in which the height of each student was measured in centimeters and those heights were matched with the same students’ scores on the first statistics test. If we find that r = 0, does that indicate that there is no association between those two variables?

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Textbook Question

Testing for a Linear Correlation

In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of α = 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 10-2 exercises.)

Powerball Jackpots and Tickets Sold Listed below are the same data from Table 10-1 in the Chapter Problem, but an additional pair of values has been added from actual Powerball results. Is there sufficient evidence to conclude that there is a linear correlation between lottery jackpots and numbers of tickets sold? Comment on the effect of the added pair of values in the last column. Compare the results to those obtained in Example 4.

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Textbook Question

Exercises 1–10 are based on the following sample data consisting of costs of dinner (dollars) and the amounts of tips (dollars) left by diners. The data were collected by students of the author.

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Fixed Percentage If a restaurant were to change its tipping policy so that a constant tip of 20% of the bill is added to the cost of the dinner, what would be the value of the linear correlation coefficient for the paired amounts of dinners/tips?

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