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- Aspirin III: Decision and Conclusion Regarding the experiment in the data frame Aspirin from the abd package, the researchers wanted to know whether or not taking aspirin affects one's risk of developing cancer. Recall that they defined their parameters as follows: p1 = the proportion of ALL individuals who would develop cancer, if all of them were to take aspirin like the subjects in the Aspirin group did. p2 = the proportion of ALL individuals who would develop cancer, if all of them were to take a placebo, like the subjects in the placebo group did. They ran the code for a two-sided significance test and got the following results: ## ## ## Inferential Procedures for the Difference of Two Proportions p1-p2:## cancer grouped by treatment ## ## ## Descriptive Results:## ## yes n estimated.prop## Aspirin 1438 19934 0.07214## Placebo 1427 19942 0.07156## ## ## Inferential Results:## ## Estimate of p1-p2: 0.0005805 ## SE(p1.hat - p2.hat): 0.002586 ## ##…(a) There are many situations in which we want to compare means from populations having standard deviations that are equal. This method applies even if the standard deviations are known to be only approximately equal. Consider a report regarding average incidence of fox rabies in two regions. For region I, n, = 14, x, = 4.75, and s, = 2.84 and for region II, n2 = 13, x2 = 3.95, and sz = 2.41. The two sample standard deviations are sufficiently close that we can assume o, = 0,. Use the method of pooled standard deviation to consider the report, testing if there is a difference in population mean average incidence of rabies at the 5% level of significance. (Round your answer to three decimal places.) It =pare percentage differences between 2 or more categories of an independent variable), the following statistical test should be used: a. Simple linear regression b. Pearson correlation coefficient c. T test d. Chi-square test
- The average income of a large sample of households is $63,000 and the s.d. is $7,000. Assume that the data is approximately bell-shaped. What percent of these households have incomes between $42,000 and $77,000? Don’t forget to properly justify your answer using the empirical rule.Herbal cancer A report in the New England Journal of Medicine notes growing evidence that the herb Aris-tolochia fangchi can cause urinary tract cancer in those who take it. Suppose you are asked to design an experi-ment to study this claim. Imagine that you have data on urinary tract cancers in subjects who have used thisherb and similar subjects who have not used it and thatyou can measure incidences of cancer and precancerouslesions in these subjects. State the null and alternativehypotheses you would use in your study.Chi-square Test for a Variance or Standard Deviation: Scores on an IQ test are normally distributed. A sample of 24 IQ scores had standard deviation s = 23 . The developer of the test claims that the population standard deviation is α = 15. Do these data provide sufficient evidence to contradict this claim? Use the α = .01 level of significance.
- 8. True or False? Test Average and Quiz Average are both significantly correlated with Course %, and they are significantly correlated with each other. Dr. Wright is also interested in whether students who do well on the first test are more likely to do well in the course overall. 9. What statistical analysis should Dr. Wright use to test whether Test 1 was a significant predictor of Course %? A- Spearman Correlation B- Regression C- Chi-Square goodness of fit D- Oneway ANOVADiscussion Question: In this research study, one group was asked to watch a car accident and were asked to estimate the speed of the car after it "hit" the other car, while a different group also watched an accident but instead were asked to estimate the speed after the cars "collided." Explain why an independent samples t-test was used, and give your own example of a research study in which an independent samples t-test would be the appropriate statistical analysis.Further studies to determine the validity of a hypothesis concerning the occurence of disease? A. Analytic Epidemiology B. Descriptive Epidemiology C. Experimental Epidemiology pick the correct answer.
- Using the sample data from the accompanying table, complete parts (a) and (b). E Click the icon to view the data table (a) Explain why it does not make sense to construct confidence or prediction intervals based on the least-squares regression equation. Choose the correct answer below. O A. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is a linear relationship between sugar content and calories in high-protein and moderate protein energy bars. O B. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because there is no linear relationship between sugar content and calories in high-protein and moderate protein energy bars. O C. It does not make sense to construct confidence or prediction intervals based on the least-squares regression equation because the residuals are not normally distributed. (b) Construct a 95% confidence interval for…Subject; steTrue or False? If False, explain: a) The sample is the group of people on whom we wish to draw statistical interference. b) The Mean Square Error from a regression model is an example of a descriptive statistic. c) Getting enough power (so that we are able to conclude a non-zero slope in a scenario where the true slope is non-zero) is achieved primarily by increasing sample size.