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The article "Foraging Behavior of the Indian False Vampire Bat" (Biotropica \([1991]: 63-67\) ) reported that 36 of 193 female bats in flight spent more than 5 min in the air before locating food. For male bats, 64 of 168 spent more than 5 min in the air. Is there sufficient evidence to conclude that the proportion of flights longer than \(5 \mathrm{~min}\) in length differs for males and females? Test the relevant hypotheses using \(\alpha=.01\).

Short Answer

Expert verified
Yes, there is sufficient evidence at the 0.01 significance level to conclude that the proportion of flights longer than 5 minutes differs for males and females.

Step by step solution

01

State the Hypotheses

The null hypothesis \(H_0\) is that the proportion of flights longer than 5 minutes for males and females is the same, and the alternative hypothesis \(H_1\) is that they are different. In mathematical notation, these are expressed as: \(H_0: p_m = p_f\) and \(H_1: p_m \neq p_f\) where \(p_m\) is the proportion for male bats and \(p_f\) is for the female bats.
02

Calculate Sample Proportions

The sample proportion for female bats is the number of successes (flights longer than 5 minutes) divided by the number of trials, or \( \hat{p}_f = 36/193 = 0.1866 \). Similarly, for male bats, the sample proportion is \( \hat{p}_m = 64/168 = 0.3810 \)
03

Perform the Test

We will perform the two-proportion z-test. The test statistic is calculated as follows: \(Z = \frac{(\hat{p}_m - \hat{p}_f) - 0} { \sqrt{\hat{p}(1-\hat{p})(\frac{1}{n_m}+\frac{1}{n_f})}}\) where \( \hat{p} = \frac{n_m\hat{p}_m+n_f\hat{p}_f}{n_m + n_f} \). Substituting gives \( Z \approx 3.99 \)
04

Make a Decision

Compare the test statistic to a critical value from the standard normal table. The critical value for a two-tailed test at the 0.01 significance level is approximately 2.58. Since 3.99 > 2.58, we reject the null hypothesis. There is sufficient evidence at the 0.01 significance level to conclude that the proportion of flights longer than 5 minutes differs for males and females.

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Most popular questions from this chapter

A university is interested in evaluating registration processes. Students can register for classes by using either a telephone registration system or an online system that is accessed through the university's web site. Independent random samples of 80 students who registered by phone and 60 students who registered online were selected. Of those who registered by phone, 57 reported that they were satisfied with the registration process. Of those who registered online, 50 reported that they were satisfied. Based on these data, is it reasonable to conclude that the proportion who are satisfied is higher for those who register online? Test the appropriate hypotheses using \(\alpha=.05\).

The article "So Close, Yet So Far: Predictors of Attrition in College Seniors" (Journal of College Student Development \([1999]: 343-354\) ) attempts to describe differences between college seniors who disenroll before graduating and those who do graduate. Researchers randomly selected 42 nonreturning and 48 returning seniors, none of whom were transfer students. These 90 students rated themselves on personal contact and campus involvement. The resulting data are summarized here: \begin{tabular}{lcccc} & \multicolumn{2}{c} { Returning \((n=48)\)} & & Nonrefurning \((n=42)\) \\ \cline { 2 } \cline { 4 - 5 } & & Standard & & Standard \\ & Mean Deviation & & Mean & Deviation \\ \hline Personal & & & & \\ Contact & \(3.22\) & \(.93\) & & \(2.41\) & \(1.03\) \\ Campus & & & & \\ Involvement & \(3.21\) & \(1.01\) & \(3.31\) & \(1.03\) \\ & & & & \end{tabular} a. Construct and interpret a \(95 \%\) confidence interval for the difference in mean campus involvement rating for returning and nonreturning students. Does your interval support the statement that students who do not return are less involved, on average, than those who do? Explain. b. Do students who don't return have a lower mean personal contact rating than those who do return? Test the relevant hypotheses using a significance level of \(.01\).

Are college students who take a freshman orientation course more or less likely to stay in college than those who do not take such a course? The article "A Longitudinal Study of the Retention and Academic Performance of Participants in Freshmen Orientation Courses" (Journal of College Student Development \([1994]: 444-\) 449) reported that 50 of 94 randomly selected students who did not participate in an orientation course returned for a second year. Of 94 randomly selected students who did take the orientation course, 56 returned for a second year. Construct a \(95 \%\) confidence interval for \(\pi_{1}-\pi_{2}\), the difference in the proportion returning for students who do not take an orientation course and those who do. Give an interpretation of this interval.

The paper "Effects of Fast-Food Consumption on Energy Intake and Diet Quality Among Children in a National Household Survey" (Pediatrics [2004]: \(112-118\) ) investigated the effect of fast-food consumption on other dietary variables. For a sample of 663 teens who reported that they did not eat fast food during a typical day, the mean daily calorie intake was 2258 and the sample standard deviation was \(1519 .\) For a sample of 413 teens who reported that they did eat fast food on a typical day, the mean calorie intake was 2637 and the standard deviation was 1138 . a. What assumptions about the two samples must be reasonable in order for the use of the two-sample \(t\) confidence interval to be appropriate? b. Use the given information to estimate the difference in mean daily calorie intake for teens who do eat fast food on a typical day and those who do not.

The article "Trial Lawyers and Testosterone: BlueCollar Talent in a White- Collar World" (Journal of Applied Social Psychology [1998]: 84-94) compared trial lawyers and nontrial lawyers on the basis of mean testosterone level. Random samples of 35 male trial lawyers, 31 male nontrial lawyers, 13 female trial lawyers, and 18 female nontrial lawyers were selected for study. The article includes the following statement: "Trial lawyers had higher testosterone levels than did nontrial lawyers. This was true for men, \(t(64)=3.75, p<.001\), and for women, \(t(29)=2.26, p<.05 . "\) a. Based on the information given, is there a significant difference in the mean testosterone level for male trial and nontrial lawyers? b. Based on the information given, is there a significant difference in the mean testosterone level for female trial and nontrial lawyers? c. Do you have enough information to carry out a test to determine whether there is a significant difference in the mean testosterone levels of male and female trial lawyers? If so, carry out such a test. If not, what additional information would you need to be able to conduct the test?

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