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For each of the following pairs of variables, indicate whether you would expect a positive correlation, a negative correlation, or a correlation close to \(0 .\) Explain your choice. a. Maximum daily temperature and cooling costs b. Interest rate and number of loan applications c. Incomes of husbands and wives when both have fulltime jobs d. Height and IQ e. Height and shoe size f. Score on the math section of the SAT exam and score on the verbal section of the same test g. Time spent on homework and time spent watching television during the same day by elementary school children h. Amount of fertilizer used per acre and crop yield (Hint: As the amount of fertilizer is increased, yield tends to increase for a while but then tends to start decreasing.)

Short Answer

Expert verified
a. Positive correlation; b. Negative correlation; c. Positive correlation; d. Correlation close to 0; e. Positive correlation; f. Positive correlation; g. Negative correlation; h. Initially positive then negative correlation.

Step by step solution

01

Analyzing the Relationship between Maximum Daily Temperature and Cooling Costs

As the maximum daily temperature increases, the need for cooling also increases, thus raising the cooling costs, indicating a positive correlation.
02

Analyzing the Relationship between Interest Rate and Number of Loan Applications

When interest rates are high, loans become expensive and hence the number of loan applications may decrease. This suggests a negative correlation.
03

Analyzing the Relationship between Incomes of Husbands and Wives

If both husbands and wives have full-time jobs, their incomes might be similar or depend on the similar economical conditions, indicating a likely positive correlation.
04

Analyzing the Relationship between Height and IQ

Height and IQ are two different variables that don't seem to affect each other significantly. Hence, a correlation close to 0 would be expected.
05

Analyzing the Relationship between Height and Shoe Size

Usually, taller people tend to have larger shoe sizes. Thus, it is likely to expect a positive correlation between height and shoe size.
06

Analyzing the Relationship between Scores on Different Sections of the SAT Exam

Performing well on one section of the SAT may likely indicate good performance on other sections too, indicating a potential positive correlation.
07

Analyzing the Relationship between Time Spent on Homework and Time Spent Watching Television

If more time is spent on watching television, it might mean less time for homework, suggesting a negative correlation.
08

Analyzing the Relationship between Amount of Fertilizer Used and Crop Yield

While initially an increase in the amount of fertilizer might boost the crop yield, excessive use of fertilizer may have an adverse effect, indicating a positive correlation initially followed by a negative correlation.

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Most popular questions from this chapter

The article "Cost-Effectiveness in Public Education" (Chance [1995]: \(38-41\) ) reported that for a regression of \(y=\) average SAT score on \(x=\) expenditure per pupil, based on data from \(n=44\) New Jersey school districts, \(a=766, b=0.015, r^{2}=.160\), and \(s_{e}=53.7\) a. One observation in the sample was \((9900,893)\). What average SAT score would you predict for this district, and what is the corresponding residual? b. Interpret the value of \(s_{e}\). c. How effectively do you think the least-squares line summarizes the relationship between \(x\) and \(y ?\) Explain your reasoning.

Explain why it can be dangerous to use the leastsquares line to obtain predictions for \(x\) values that are substantially larger or smaller than those contained in the sample.

The relationship between hospital patient-to-nurse ratio and various characteristics of job satisfaction and patient care has been the focus of a number of research studies. Suppose \(x=\) patient-to-nurse ratio is the predictor variable. For each of the following potential dependent variables, indicate whether you expect the slope of the least-squares line to be positive or negative and give a brief explanation for your choice. a. \(y=\) a measure of nurse's job satisfaction (higher values indicate higher satisfaction) b. \(y=\) a measure of patient satisfaction with hospital care (higher values indicate higher satisfaction) c. \(y=\) a measure of patient quality of care.

The paper "Postmortem Changes in Strength of Gastropod Shells" (Paleobiology [1992]: \(367-377\) ) included scatterplots of data on \(x=\) shell height (in centimeters) and \(y=\) breaking strength (in newtons) for a sample of \(n=38\) hermit crab shells. The least-squares line was \(\hat{y}=-275.1+244.9 x\) a. What are the slope and the intercept of this line? b. When shell height increases by \(1 \mathrm{~cm}\), by how much does breaking strength tend to change? c. What breaking strength would you predict when shell height is \(2 \mathrm{~cm} ?\) d. Does this approximate linear relationship appear to hold for shell heights as small as \(1 \mathrm{~cm} ?\) Explain.

Is the following statement correct? Explain why or why not. A correlation coefficient of 0 implies that no relationship exists between the two variables under study.

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