# Chapter 9

30258 words 122 pages
Exam 1. 1. All continuous random variables are normally distributed. False. 2. The actual weight of hamburger patties is an example of a continuous random variable. True 3. The college of business administration at acorn University offers a major in finance. Based on historical records, 30% of the college of business students major in Finance. A random sample of 20 students is selected. What is the probability that exactly 3 of the selected students are majoring in Finance? .0716 4. Assume that we have selected a random sample of 25 units from a normally distributed large population. If u = 15, and c2=4, what is the probability that we will obtain a sample mean of less than 14? .0062 5. The normal approximation of the binomial distribution …show more content…

Student response: Percent Value 0.0% 100.0% 0.0% Correct Response Student Response Answer Choices a. b. c. Wider than Narrower than Equal to

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4/4

Question 6

(4 points)

When the null hypothesis is true, there is no possibility of making a Type I error. Student response: Percent Value 0.0% 100.0% Correct Response Student Response Answer Choices a. b. True False

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4/4

Question 7

(4 points)

What sample size would be required to estimate µ to within ± 3 with 95% confidence if the population standard deviation is 24.5? Student response: Percent Value 0.0% 0.0% 100.0% 0.0% 0.0% Correct Response Student Response Answer Choices a. b. c. d. e. 769 124 257 91 2321

Score:

4/4

Question 8

(4 points)

According to a recent major survey, 70% of the respondents indicated that there is too much violence on TV. For a random sample of 40 people, what is the 95% confidence interval of the proportion of people who feel that there is too much violence on TV? Student response: Percent Value 0.0% 0.0% 0.0% 100.0% 0.0% Correct Response Student Response Answer Choices a. b. c. d. e. .70 ± .12 .70 ±.03 .70 ±.90 .70 ±.14 .70 ± .07

Score:

4/4

Question 9

(4 points)

Alpha ( ) is the probability that the test statistic would assume a value as or more extreme than the observed value of

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