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**Unformatted text preview: **1 Displaying Data - Solutions 1 Suppose a medical researcher compares the average blood pressures of women who take oral contraceptives to the blood pressures of women who do not. a. Is blood pressure a categorical variable or a quantitative variable and which graph(s) would be most appropriate to use to display the data? Quantitative; we would measure blood pressure. If we categorized the values (e.g. low, medium, high) then this would be a categorical variable. Best graphs would be histogram, boxplot, or stem and leaf b. Is oral contraceptive use (or not) a categorical variable or a quantitative variable and which graph(s) would be most appropriate to use to display the data? Categorical; data produced from yes/no questions are categorical. Best graphs would be pie chart or bar chart c. What variables that affect blood pressure might confuse the comparison of average blood pressures for users and nonusers? That is, what factors affecting blood pressure might differ for users and nonusers. Explain. Answers will vary. One possibility is age. Age affects blood pressure and also there may age differences between users and non-users of oral contraceptives. 2 A statistics class at UC Davis was asked About how many hours do you watch television per week? A five-number summary of the responses from 173 students follows. Median 6 Quartiles 2 12.5 Extremes 100 a. What were the median hours of weekly television watching? In the context of this situation, write a sentence that interprets the median. Median = 6. About 50% of the class watched 6 or less hours per week. b. Give the value that completes the following sentence. About 1/4 of the students watch less than ___ hours of television per week. 2 (lower quartile, Q1) since Q1 represents the first quartile which is the value where 25% of the data falls at or below. c. Give the value that completes the following sentence. About 1/4 of the students watch more than ___ hours of television per week. 12.5 (upper quartile, Q3) since Q3 represents the third quartile which is the value where 75% of the data falls at or below, and conversely 25% watch at or above. ...

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