Elementary Statistics
12th Edition
ISBN: 9780321836960
Author: Mario F. Triola
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 9.5, Problem 11BSC
To determine
To test: The claim that those given sham treatment have pain reductions that vary more than the pain reductions for those treated with magnets.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Starfish coildots is a disease affecting approximately 40 different species of sea stars and several other echinoderms. A sample of 240 ochre starfish and 155 sunflower starfish found that 97 ochre starfish and 54 sunflower starfish showed signs of infection.
Is there evidence to suggest that the difference in the proportion of infected ochre starfish is greater than the proportion of infected sunflower starfish?
(a) Define the parameter(s) of interest using the correct notation. Then, state the null and alternative hypotheses for this study.
(b) Calculate the observed test statistic and state the distribution it follows (including degrees of freedom, if needed).
(c) Give the p-value, or a range of appropriate values for the p-value.
(d) Using the significance level α = 0.10, state your conclusions regarding the proportion of infected starfish in a plain English sentence.
(e) Determine the 90% confidence interval for the difference in the proportions of infected ochre starfish and…
City Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9–12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements” in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi /gal).
If exactly two predictor (x) variables are to be used to predict the city fuel consumption, which two variables should be chosen? Why?
City Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9–12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements” in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi /gal).
Which regression equation is best for predicting city fuel consumption? Why?
Chapter 9 Solutions
Elementary Statistics
Ch. 9.2 - Verifying Requirements In the largest clinical...Ch. 9.2 - Verifying Requirements In the largest clinical...Ch. 9.2 - Hypotheses and Conclusions Refer to the hypothesis...Ch. 9.2 - Using Confidence Intervals a. Assume that we want...Ch. 9.2 - Interpreting Displays. In Exercises 5 and 6, use...Ch. 9.2 - Interpreting Displays. In Exercises 5 and 6, use...Ch. 9.2 - Testing Claims About Proportions. In Exercises...Ch. 9.2 - Prob. 8BSCCh. 9.2 - Testing Claims About Proportions. In Exercises...Ch. 9.2 - Testing Claims About Proportions. In Exercises...
Ch. 9.2 - Testing Claims About Proportions. In Exercises...Ch. 9.2 - Prob. 12BSCCh. 9.2 - Tennis Challenges Since the Hawk-Eye instant...Ch. 9.2 - Police Gunfire In a study of police gunfire...Ch. 9.2 - Testing Claims About Proportions. In Exercises...Ch. 9.2 - Testing Claims About Proportions. In Exercises...Ch. 9.2 - Testing Claims About Proportions. In Exercises...Ch. 9.2 - Marathon Finishers In a recent New York City...Ch. 9.2 - Overlap of Confidence Intervals In the article On...Ch. 9.2 - Equivalence of Hypothesis Test and Confidence...Ch. 9.2 - Determining Sample Size The sample size needed to...Ch. 9.3 - Independent and Dependent Samples Which of the...Ch. 9.3 - Interpreting Confidence Intervals If the heights...Ch. 9.3 - Interpreting Confidence Intervals What does the...Ch. 9.3 - Hypothesis Tests and Confidence Intervals a. In...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - Prob. 6BSCCh. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - Prob. 8BSCCh. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - Prob. 10BSCCh. 9.3 - Prob. 11BSCCh. 9.3 - Prob. 12BSCCh. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - In Exercises 5-20, assume that the two samples are...Ch. 9.3 - Prob. 21BSCCh. 9.3 - Large Data Sets. In Exercises 21-24, use the...Ch. 9.3 - Large Data Sets. In Exercises 21-24, use the...Ch. 9.3 - Large Data Sets. In Exercises 21-24, use the...Ch. 9.3 - Prob. 25BBCh. 9.3 - Pooling. In Exercises 25 and 26, assume that the...Ch. 9.3 - Prob. 27BBCh. 9.3 - Prob. 28BBCh. 9.3 - Prob. 29BBCh. 9.4 - True Statements? For the methods of this section,...Ch. 9.4 - Prob. 2BSCCh. 9.4 - Prob. 3BSCCh. 9.4 - Confidence Intervals If we use the sample data in...Ch. 9.4 - Prob. 5BSCCh. 9.4 - Prob. 6BSCCh. 9.4 - Calculations with Paired Sample Data. In Exercises...Ch. 9.4 - Prob. 8BSCCh. 9.4 - Prob. 9BSCCh. 9.4 - Prob. 10BSCCh. 9.4 - Prob. 11BSCCh. 9.4 - Prob. 12BSCCh. 9.4 - In Exercises 920, assume that the paired sample...Ch. 9.4 - In Exercises 920, assume that the paired sample...Ch. 9.4 - In Exercises 516, use the listed paired sample...Ch. 9.4 - Prob. 16BSCCh. 9.4 - In Exercises 920, assume that the paired sample...Ch. 9.4 - In Exercises 920, assume that the paired sample...Ch. 9.4 - In Exercises 920, assume that the paired sample...Ch. 9.4 - In Exercises 920, assume that the paired sample...Ch. 9.4 - Prob. 21BSCCh. 9.4 - Prob. 22BSCCh. 9.4 - Prob. 23BSCCh. 9.4 - Prob. 24BSCCh. 9.4 - Prob. 25BBCh. 9.5 - F Test Statistic a. If s12 represents the larger...Ch. 9.5 - F Test If using Data Set 1 in Appendix B for a...Ch. 9.5 - Prob. 3BSCCh. 9.5 - Prob. 4BSCCh. 9.5 - Prob. 5BSCCh. 9.5 - Prob. 6BSCCh. 9.5 - Hypothesis Tests of Claims About Variation. In...Ch. 9.5 - Prob. 8BSCCh. 9.5 - Prob. 9BSCCh. 9.5 - Prob. 10BSCCh. 9.5 - Prob. 11BSCCh. 9.5 - Prob. 12BSCCh. 9.5 - Prob. 13BSCCh. 9.5 - Prob. 14BSCCh. 9.5 - Hypothesis Tests of Claims About Variation. In...Ch. 9.5 - Prob. 16BSCCh. 9.5 - Prob. 17BSCCh. 9.5 - Prob. 18BSCCh. 9.5 - Prob. 19BBCh. 9.5 - Prob. 20BBCh. 9.5 - Prob. 21BBCh. 9 - In Exercises 1-4, use the following surrey...Ch. 9 - In Exercises 1-4, use the following surrey...Ch. 9 - In Exercises 1-4, use the following surrey...Ch. 9 - In Exercises 1-4, use the following survey...Ch. 9 - Listed below are the costs (in dollars) of...Ch. 9 - Prob. 6CQQCh. 9 - Prob. 7CQQCh. 9 - Prob. 8CQQCh. 9 - Prob. 9CQQCh. 9 - Prob. 10CQQCh. 9 - Prob. 1RECh. 9 - Prob. 2RECh. 9 - Airbags Save Lives In a study of the effectiveness...Ch. 9 - Are Flights Cheaper When Scheduled Earlier? Listed...Ch. 9 - Self-Reported and Measured Female Heights As part...Ch. 9 - Eyewitness Accuracy of Police Does stress affect...Ch. 9 - Prob. 7RECh. 9 - Effect of Blinding Among 13,200 submitted...Ch. 9 - Comparing Means The baseline characteristics of...Ch. 9 - Comparing Variation Use the sample data from...Ch. 9 - Heights of Mothers and Daughters. In Exercises...Ch. 9 - Prob. 2CRECh. 9 - Prob. 3CRECh. 9 - Heights of Mothers and Daughters. In Exercises...Ch. 9 - Prob. 5CRECh. 9 - Dark Survey In a survey of 1032 Americans,...Ch. 9 - Backup Generator The USA Today web site posted...Ch. 9 - Juke Survey Late-night talk show host David...Ch. 9 - Normal Distribution Based on the measurements in...Ch. 9 - Prob. 10CRECh. 9 - Prob. 1FDDCh. 9 - Critical Thinking: Ages of workers killed in the...Ch. 9 - Critical Thinking: Ages of workers killed in the...Ch. 9 - Prob. 4FDDCh. 9 - Prob. 5FDDCh. 9 - Prob. 6FDD
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- City Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9–12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements” in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi /gal). A Honda Civic weighs 2740 lb, it has an engine displacement of 1.8 L, and its highway fuel consumption is 36 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate?arrow_forward3. Regression analysis breaks scores on the DV into... (explain and give equations)arrow_forwardPlease show me your solutions and interpretations. Show the completehypothesis-testing procedure.An article in the ASCE Journal of Energy Engineering (1999, Vol. 125, pp. 59–75) describes a study of the thermal inertia properties of autoclaved aerated concrete used as a building material. Five samples of the material were tested in a structure, and the average interior temperatures (°C) reported were as follows: 23.01, 22.22, 22.04, 22.62, and 22.59. Test that the average interior temperature is equal to 22.5 °C using α = 0.05.arrow_forward
- Eyeglassomatic manufactures eyeglasses for different retailers. They test to see how many defective lenses they made in a time period. Table #4.2.2 gives the defect and the number of defects. Table #4.2.2: Number of Defective Lenses Defect type Number of defects Scratch 5865 Right shaped – small 4613 Flaked 1992 Wrong axis 1838 Chamfer wrong 1596 Crazing, cracks 1546 Wrong shape 1485 Wrong PD 1398 Spots and bubbles 1371 Wrong height 1130 Right shape – big 1105 Lost in lab 976 Spots/bubble – intern 976 Find the probability of picking a lens that is scratched or flaked. Find the probability of picking a lens that is the wrong PD or was lost in lab. Find the probability of picking a lens that is not scratched. Find the probability of picking a lens that is not the wrong shape.arrow_forward#20 part b only- show full work for psych statsarrow_forwardResearchers examined bone strength by collecting 10 cadaveric femurs from subjects in each of three age groups: young (19–49 years), middle-aged (50–69 years), and elderly (70 years or older). One of the outcome measures was the force in Newtons required to fracture the bone. At α = 0.05, test the claim that the bone strengths differ among the age groups. 10. What is the dependent variable? _____________________11. What is/are the independent variable/s? _________________________12. What type of ANOVA is appropriate? ___________________________13. Do the appropriate assumption check and interpret the result based on the p value.______________________________________________________________________14. What is the critical value? (Round off to 3 decimal places.) ________15. What is the p value? (Key in the value as it appears in JASP.) ________16. Interpret the F statistic based on the critical value and make a…arrow_forward
- (Please answer 2nd question ) 1. Assume that there are two types of driver: One is careful and has a 0.1% of being in an accident. The other type is careless and has a 1% chance of being in an accident. Assume that each type represents 50% of the population. If there is a law mandating that all drivers buy insurance that would cover $100,000 in damages, the actuarially far premium for all drivers would be ________ while if there were no such law, the fair premium would be __________. Group of answer choices A) $100, $1,000 B) $100, somewhere between $100 and $1,000 C) $550, somewhere between $550 and $1,000 D) $550, 1,000 Ans :- option c ). 2. The term(s) used to describe the problem(s) that make the actuarially fair premiums different in the two cases in the question above is(are) Group of answer choices A) Asymmetric information B) Moral hazard C) Adverse selection D) A, B, and C E) A and Carrow_forwardResearchers examined bone strength by collecting 10 cadaveric femurs from subjects in each of three age groups: young (19–49 years), middle-aged (50–69 years), and elderly (70 years or older). One of the outcome measures was the force in Newtons required to fracture the bone. At α = 0.05, test the claim that the bone strengths differ among the age groups.arrow_forward"Based on recent data, 80% of all part-time college students are female. A survey of 1000 college students in Kentucky found that 72% of part-time college students were female." What is the parameter? What is the statistic? What statistic are we interested in? p or Xarrow_forward
- How can we make predictions using a fitted model in R?arrow_forwardPlease solve part d and e only. The body mass index (BMI) of a person is defined to be the person’s body mass divided by the square of the person’s height. The article “Influences of Parameter Uncertainties within the ICRP 66 Respiratory Tract Model: Particle Deposition” (W. Bolch, E. Farfan, et al., Health Physics, 2001:378–394) states that body mass index (in kg/m2) in men aged 25–34 is lognormally distributed with parameters μ = 3.215 and σ = 0.157. a.Find the mean and standard deviation BMI for men aged 25–34. b.Find the standard deviation of BMI for men aged 25–34. c.Find the median BMI for men aged 25–34. d.What proportion of men aged 25–34 have a BMI less than 20? e.Find the 80th percentile of BMI for men aged 25–34.arrow_forwardEconometrics, Bruce Hansen exercise 7.8arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY