Ch 09 Answers - Chapter 9 One-Sample Hypothesis Tests 9.1...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Chapter 9 One-Sample Hypothesis Tests 9.1 Graphs should show a normal distribution with a mean of 80. a. Rejection region in the lower tail. b. Rejection region in both tails. c. Rejection region in the upper tail. 9.2 a. .05*1000 = 50 times b. .01*1000 = 10 times c. .001*1000 = 1 time 9.3 a. Null hypothesis the man is not having a heart attack. Type I error: I admit him when he does not have a heart attack. Type II error: I fail to admit him, he does have a heart attack, and dies. Better to make a Type I than Type II error, since a type II error is fatal. b. Type I error: I reject the null and let them land even though they could have stayed up for 15 minutes (or more). Type II Don’t let the plane land and the plane runs out of fuel. It is more costly to make a Type II error. c. Type I error: I reject the null and rush out to Staples, get caught in the snow and fail to finish the report (when if I had stayed I would have finished it). Type II error: I run out of ink and can’t finish the report. Better to stay and try to finish the report, in fact better to print out some of it than none of it. 9.4 Costly improvements may be too small to be noticed by customers and they may be unwilling to pay for the improvement. 9.5 a. Null hypothesis: Employee is not using illegal drugs. Alternative hypothesis: Employee is using illegal drugs. b. Type I error: Test is positive for drugs when no drugs are being used by the individual Type II error: Test is negative for drug use when the person is using drugs. c. I might dismiss or discipline someone who is a non-drug user (Type I error). They could sue for wrongful damages. I might keep on someone who should be dismissed and they cause serious injury via a work related accident to themselves or others (Type II error). A Type II error could have more serious consequences than a Type I error. 9.6 a. Null hypothesis: There is no fire. Alternative hypothesis: There is a fire. b. Type I error: A smoke detector sounds an alarm when there is no fire. Type II error: A smoke detector does not sound an alarm when there is a fire. c. Consequence of making a type I error is that some guests will be inconvenienced by a false alarm and there is the cost of having the fire department summoned. Consequence of making a type II error is that the hotel will burn down and perhaps kill or injure many. d. Reducing β risk would increase the likelihood making a Type I error, increasing the likelihood of a false alarm. Guests of the hotel and perhaps the fire department would be affected. 9.7 a. .25 .2 2.0 .2*.8 100 z - = = . From Appendix C: p -value = .046. b. z = 1.90, p -value = .9713 c. z = 1.14, p -value = .1271 76
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
9.8 a. .7 .6 1.83 .6*.4 80 z - = = . From Appendix C: p -value = .0339. b.
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 12/13/2010 for the course LEEDS BCOR 1020 taught by Professor Heatheradams during the Spring '08 term at Colorado.

Page1 / 9

Ch 09 Answers - Chapter 9 One-Sample Hypothesis Tests 9.1...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online