A researcher studied iron-deficiency anemia in women in each of two developing countries. Differences in the dietary habits between the two countries led the researcher to believe that anemia is less prevalent among women in the first country than among women in the second country. A random sample of 1900 women from the first country yielded 456 women with anemia, and an independently chosen, random sample of 2500 women from the second country yielded 617 women with anemia. Based on the study can we conclude, at the 0.10 level of significance, that the proportion p, of women with anemia in the first country is less than the proportion p, of women with anemia in the second country? Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places and round your answers as specified in the parts below. (If necessary, consult a list of formulas.) (a) State the null hypothesis H, and the alternative hypothesis H,. H, :0 H :0 Do (b) Determine the type of test statistic to use. (Choose one) ▼ D=0 OSO (c) Find the value of the test statistic. (Round to three or more decimal places.) O

In a survey of working parents (both parents working), one of the questions asked was "Have you refused a job, promotion, or transfer because it would mean less time with your family?" 410410 men and 410410 women were asked this question. 26%26% of the men and 19%19% of the women responded "Yes". Based on this survey, can it be concluded that there is a difference in the proportion of men ( p1p1 ) and women ( p2p2 ) responding "Yes"? Use a significance level of α=0.05α=0.05 for the test. Step 3 of 5 :   Compute the value of the test statistic. Round your answer to two decimal places.

Results from the National Health and Nutrition Examination Survey (NHANES) conducted thirty years ago revealed that out of 378 randomly selected adults in the United States 57 were considered to be obese. In this year’s National Health and Nutrition Examination Survey, out of 426randomly selected adults in the United States 135 were considered to be obese. Based on these results, can one conclude, at the 0.01 level of significance, that the percentage of adults in the United States that are obese is considerably higher now than it was thirty years ago?

A large clinical trial of the effect of diet on breast cancer assigned women at random to either a normal diet or a low-fat diet. To check that the random assignment did produce comparable groups, we can compare the two groups at the start of the study. Asked if there is a family history of breast cancer: 1276 of the 5964 women in the low-fat group and 1507 of the 7726 women in the control group said "Yes." If the random assignment worked well, there should not be a significant difference in the proportions with a family history of breast cancer. How significant is the observed difference? State: Is there evidence of a difference in the proportion of women with a family history of breast cancer between the treatment and control groups? Plan: Let pi be the proportion for the treatment group, and Pz the proportion for the control group. State the hypotheses for your test. Ha:Pi + P2 Solve: Give the value of the test statistic. Use the calculator. Select an answer ♥ Ho:pi = p2 What is the…

According to the American Lung association, lung cancer account for 28% of all cancer deaths in the US.  A new type of screening for lung cancer, computed tomography (CT), has been developed.  Medical researchers believe CT scans are scans are more sensitive than regular X-rays in pinpointing small tumors. The Cancer Center at the University of South Florida is currently conducting a clinical trial of 50,000 smokers nationwide to compare the effectiveness of CT scans with X-ray for detecting lung cancer (Today’s Tomorrows, Fall 2002).  Each participating smoker is randomly assigned to one of the two screening methods, CT or chest X-ray, and his or her progress is tracked over time.  The age at which the scanning method first detects a tumor is the variable of interest. A. Identify the data collection method used by the cancer researchers.        B. dentify experimental units of the study.  C. Identify the type of the variable measured.  D. Identify the population and sample.

Mammography and clinical breast examination are the two major techniques used to screen for breast cancer. However, as true for any screening test, they are not completely accurate. If it is determined, based on mammographic findings, that there is a possibility of breast cancer, this is usually confirmed or disconfirmed by a subsequent biopsy. A false positive test is a mammogram positive test that is disconfirmed by biopsy. The data in Table 1 were reported in a paper concerning breast cancer screening (Elmore, et al, New England Journal of Medicine 1998; 338(16): 1089-1096). Table 1 False positive breast cancer screening tests over a 10-year period # Screening tests # False positive tests 9762 631 1. Suppose 10 women are given mammograms. What is the probability that at least 1 woman will have a false positive test?

Acne is a common skin disease that affects most adolescents and can continue into adulthood. A study compared the effectiveness of three acne treatments and a placebo, all in gel form, applied twice daily for 12 weeks. The study's 517 teenage volunteers were randomly assigned to one of the four treatments. Success was assessed as clear or almost clear skin at the end of the 12 week period. The results of the study can be seen in the table below. Using the appropriate statistical test, determine if there is significant evidence that the four treatments perform differently. If so, how do they compare.

NCI Cancer Bulletin, December 2, 2008 Volume 5 / Number 24 Title of the article: After Menopause, Weight Affects Breast Cancer Rates More than Mammography Use   Women who are overweight or obese after menopause face an increased risk of breast cancer, but a large prospective cohort study indicates that the frequency of mammography use and screening accuracy are not the primary explanations for higher rates of breast cancer in these women. The same is true of large, invasive breast cancer tumors and advanced stage disease; risk increases with weight, but higher rates are not explained by the frequency or accuracy of screening mammography before breast cancer was diagnosed. The study appears in the December 3 Journal of the National Cancer Institute.   Dr. Karla Kerlikowske of the San Francisco Veterans Affairs Medical Center and colleagues gathered data on 287,115 postmenopausal women who were registered in the Breast Cancer Surveillance Consortium database. Reflecting a trend in the…

NCI Cancer Bulletin, December 2, 2008 Volume 5 / Number 24 Title of the article: After Menopause, Weight Affects Breast Cancer Rates More than Mammography Use   Women who are overweight or obese after menopause face an increased risk of breast cancer, but a large prospective cohort study indicates that the frequency of mammography use and screening accuracy are not the primary explanations for higher rates of breast cancer in these women. The same is true of large, invasive breast cancer tumors and advanced stage disease; risk increases with weight, but higher rates are not explained by the frequency or accuracy of screening mammography before breast cancer was diagnosed. The study appears in the December 3 Journal of the National Cancer Institute.   Dr. Karla Kerlikowske of the San Francisco Veterans Affairs Medical Center and colleagues gathered data on 287,115 postmenopausal women who were registered in the Breast Cancer Surveillance Consortium database. Reflecting a trend in the…

Mood variation is related to photoperiod in some people, and the likelihood of depression increases in the winter months. As a result, people often assume that suicide rates increase in winter. A study in Finland (Valtonen et al. 2006) divided the year 1997 into equal halves and compared the number of suicides in “winter” (24 September to 19 March) and “summer” (remainder of year). Out of a total of 1636 suicides, 766 were in winter and 870 were in the summer. Based on these data, estimate the proportion of suicides that occurred in winter, assuming that the suicides were independent. Are the data compatible with a greater suicide rate in winter than summer, based on a 95% confidence interval?