The negative effects of ambient air pollution on children’s lung
- a. Calculate and interpret a 95% (two-sided) confidence interval for true average FEV1 level in the population of all children from which the sample was selected. Does it appear that the parameter of interest has been accurately estimated?
- b. Suppose the investigators had made a rough guess of 320 for the value of s before collecting data. What
sample size would be necessary to obtain an interval width of 50 ml for a confidence level of 95%?
Trending nowThis is a popular solution!
Chapter 7 Solutions
Student Solutions Manual for Devore's Probability and Statistics for Engineering and the Sciences, 9th
- Anemia (low healthy blood cells or hemoglobin) has an important role in exercise performance. However, the direct link between rapid changes of hemoglobin and exercise performance is still unknown. A study investigated 18 patients with a blood disorder (beta-thalassemia). Participants in the study performed an exercise test before and the day after receiving a blood transfusion. Data are given in the table. HB = Hemoglobin RER = Respiratory exchange ID Change in HB Obese RER > 1.1 ratio No No 1 -1.4 No -1.5 No Yes No Yes 3 -2 No 4 -2.1 No -1.9 Yes Yes No -1.6 -1.8 -0.8 6 7 No Yes No Yes 8 9. -1 No No -1.2 No Yes 10 11 No No -0.8 -1.5 12 Yes No No Yes 13 14 -1.4 -2.6 -1.7 No No Yes Yes 15 Yes No Yes Yes 16 -2.6 No 17 18 -2.7 -1.5 Noarrow_forwardHeight and Breast Cancer. In the article “Height and Weight at Various Ages and Risk of Breast Cancer” (Annals of Epidemiology, Vol. 2, pp. 597–609), L. Brinton and C. Swanson discussed the relationship between height and breast cancer. The study, sponsored by the National Cancer Institute, took 5 years and involved more than 1500 women with breast cancer and 2000 women without breast cancer; it revealed a trend between height and breast cancer: “. . . taller women have a 50 to 80 percent greater risk of getting breast cancer than women who are closer to 5 feet tall.” Christine Swanson, a nutritionist who was involved with the study, added, “. . . height may be associated with the culprit, . . . but no one really knows” the exact relationship between height and the risk of breast cancer. a. Classify this study as either an observational study or a designed experiment. Explain your answer. b. Interpret the statement made by Christine Swanson in light of your answer to part (a).arrow_forwardPassive exposure to environmental tobacco smoke has been associated with growth suppression and an increased frequency of respiratory tract infections in normal children. Is this association more pronounced in children with cystic fibrosis? To answer this question, 43 children (18 girls and 25 boys) attending a 2-week summer camp for cystic fibrosis patients were studied (New England Journal of Medicine, Sept. 20, 1990). Among several variables measured were the child's weight percentile (y) and the number of cigarettes smoked per day in the child's home (x). a. For the 18 girls, the coefficient of correlation between y and x was reported as r = –.50. Interpret - this result. b. Refer to part a. The p-value for testing Ho: p = 0 against H;: p # 0 was reported as p = .03. n Interpret this result. c. For the 25 boys, the coefficient of correlation between y and x was reported asr = -.12. Interpret %3D %3D this result. d. Refer to part c. The p-value for testing Ho: p = 0 against Ha: p #…arrow_forward
- Could it be that smoking actually increases survival rates among women? The accompanying data represent the 20-year survival status and smoking status of 1334 women who participated in a 20-year cohort study. Complete parts (a) through (e).arrow_forwardEfforts by airlines to improve on-time arrival rates are showing results. Boston.com reports that in the first 10 months of 2012 on-time arrival rates at U.S. airports were the highest they have been since 2003. During this period 82% of flights landed within 15 minutes of their scheduled time. Are there differences among the major airlines? The data in Sheet 35 show the number of on-time arrivals for samples of flight taken from seven major U.S. airlines in 2012. Using a 0.05 level of significance, what is the p-value and what is your conclusion? Sheet 35 Arrivals American Airlines Continental Airlines Delta Airlines JetBlue Airlines Southwest Airlines United Airlines US Airways On-time 83 54 96 60 69 66 68 Late 16 18 21 22 23 15 12 99 72 117 82 92 81 80 Select one: a) Chi-square statistic = 4.32, p-value = 0.034, reject the null hypothesis, there is a statistically significant differences in the proportion of on-time arrivals b) Chi-square statistic = 7.370,…arrow_forwardplease help me solve sub-part darrow_forward
- 2. The city council is considering a law that would ban concealed weapons in all public facilities. A sample has been selected from the community and surveyed about support for the proposed ordinance. Is there a statistically significant relationship between age and support for the law against carrying concealed weapons (use p=.05, χ2(critical) = 3.841)? Use the five step model as a guide and write a sentence or two interpreting your results. Age Under 40 40 and older Support For 142 77 219 Against 106 170 276 248 247 495arrow_forwarda pathological video game user(PVGU) is à video game user averages 31 or more hours a week of of gameplay.arrow_forwardThe paper "A Cross-National Relationship Between Sugar Consumption and Major Depression?" (Depression and Anxiety [2002]: 118-120) concluded that there was a correlation between refined sugar consumption (calories per person per day) and annual rate of major depression (cases per 100 people) based on data from 6 countries. The following data were read from a graph that appeared in the paper: рaper: Depression Sugar Consumption Rate Country Korea 150 2.3 United States 300 3.0 France 350 4.4 Germany 375 5.0 Canada 390 5.2 New Zealand 480 5.7 Compute and interpret the correlation coefficient for this data set. . Is it reasonable to conclude that increasing sugar consumption leads to higher rates of depression? Explain. Do you have any concerns about this study that would make you hesitant to generalize these conclusions to other countries?arrow_forward
- Researchers Regine Dilla and associates wanted to determine whether consumption of cola is associated with lower bone mineral density. They looked at 1125 men and 1413 women in the Framingham Osteoporosis Study, which is a cohort that began in 1971. The first examination in this study began between 1971 and 1975, with participants returning for an examination every 4 years. Based on results of questionnaires, the researchers were able to determine cola consumption on a weekly basis. Analysis of the results indicated that women who consumed at least one cola per day (on average) had a bone mineral density that was significantly lower at the femoral neck than those who consumed less than one cola per day. The researchers did not find this relation in men. (a)Why is this a cohort study? (b)What is the response variable in this study? What is the explanatory variable? (c)Is the response variable qualitative or quantitative?arrow_forwardThe 5-year incidence of cardiovascular disease (CVD) in relation to smoking status was determined in a population sample of 1000 men, 18 years and older. At baseline, 30% of the men were classified as being current smokers and 70% as being non-smokers. At the end of the follow-up, 60 CVD events had occurred among the smokers and 70 events among the non-smokers. Construct a 2 x 2 table based on the data providedarrow_forwardA researcher is exploring the relationship of academic performance of students in an online class to several factors listed below. The digital literacy scores were measured using a digital literacy test. The speed of internet connection is measured in megabyte per second (mbps). Family stress is measured using a 10-point scale test. A higher number means higher stress. Factors Affecting Academic Performance of Students in an Online Class Speed of Academic performance Digital Literacy Score Family Stress Internet Connection Score (mbps) 3 ID 87 91 4 86 89 9. 82 80 7 4 76 77 10 8. 85 91 12 5 6. 93 89 7 83 80 29 6. 84 81 30 8. 88 86 15 4 10 76 85 22 10 The variable that is used to predict changes in another variable is known as the A. nuisance variable. B. predictor variable. C. criterion variable. D. first variable.arrow_forward
- Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt