Let's say I am studying the difference in blood glucose levels in two treatments, treatment A and treatment B. I elect to use an unpooled t-test and my results say that I reject HO. What is my conclusion about the blood glucose levels in the different treatments? O The blood glucose levels in Treatment A and Treatment B are not the same O We need to calculate a p value before we can tell O Treatment A has higher blood glucose levels than Treatment B O Treatment A and Treatment B have similar blood glucose levels
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- i asked this question but it was wrong. The answer they gave was z=2.411 and p value = .102 In a survey of families in which both parents work, one of the questions asked was, "Have you refused a job, promotion, or transfer because it would mean less time with your family?" A total of 200 men and 200 women were asked this question. "Yes" was the response given by 27% of the men and 22% of the women. Based on this survey, can we conclude that there is a difference in the proportion of men and women responding "yes" at the 0.05 level of significance? (Use Men − Women.) (a) Find z. (Round your answer to two decimal places.) Find the p-value. (Round your answer to four decimal places.) (b) State the appropriate conclusion. Fail to reject the null hypothesis. There is not significant evidence that the proportions differ.Reject the null hypothesis. There is significant evidence that the proportions differ. Fail to reject the null hypothesis. There is significant evidence that the…Here's a new idea for treating advanced melanoma, the most serious kind of skin cancer: genetically engineer white blood cells to better recognize and destroy cancer cells, then infuse these cells into patients. The subjects in a small initial study were 11 patients whose melanoma had not responded to existing treatments One outcome of this experiment is measured by a test for the presence of cells that trigger an immune response in the body and so may help fight cancer. Here are data for the 11 subjects: counts of active cells per 100,000 cells before and after infusion of the modified cells. The difference (after minus before) is the response variable. Before 17 1 4 4 22 4 1 After 41 11 2 218 22 700 17 532 37 96 108 Difference 24 10 217 18 699 13 510 33 89 107 (a) Explain why this is a matched pairs design. There were an even number of subjects. All of the subjects were related. O Half of the subjects took a placebo. O Each subject was measured before and after treatment. The…Katy is interested in Chinese language learning. She believes that the Chinese characters with different numbers of strokes may affect the reading performance. You are invited to help her to design an experiment. A)What is the independent variable (IV) in this study? If the IV is required to have THREE levels, how can you manipulate it? What is the scale of measurement of this IV? B) Please provide the operational definition for the dependent variable (DV)? How can you measure the DV you defined? What is the scale of measurement of this DV?
- A pharmaceutical company wants to test whether their the incidence of side effects (i.e. adverse events) differs between the treatment and placebo groups at the a = 0.05. Let pı = the proportion of subjects in the treatment groups who experienced at least one adverse event and let p2 = the proportion of subjects in the placebo group who experience at least one adverse event. 8 out of 30 people in the treatment group experienced at least one adverse event and 5 out of 30 people in the placebo group experienced at least one adverse event. (a) Set up the null and alternative hypothesis (using mathematical notation/numbers AND interpret them in context of the problem) (b) Calculate the test statistic (c) Calculate the critical value (d) Draw a picture of the distribution of the test statistic under Ho. Label and provide values for the critical value and the test statistic, and shade the critical region. (e) Make and justify a statistical decision at the a = 0.05 level and state your…Two types of medical devices used for knee replacement are being studied to see if the type of knee replacement used affects the rate of infection for a specific bacterial infection. The infection rate for a specific bacterial infection after surgery for device A is 0.0043. The rate for the same bacterial infection is 0.0121 for device B. How does the risk of developing the bacterial infection in individuals using device B compare to the risk of developing the bacterial infection in individuals using device A? Individuals using device A are 2.814 times more likely to develop the bacterial infection of interest than individuals using device B. Individuals using device B are 2.814 times more likely to develop the bacterial infection of interest than individuals using device A. Individuals using device A are 1.35 times more likely to develop the bacterial infection of interest than individuals using device B. Individual using device B are 1.35 times…A medical student at a community college in city Q wants to study the factors affecting the systolic blood pressure of a person (Y) Generally, the systolic blood pressure depends on the BMI of a person (B) and the age of the person A. She wants to test whether or not the BMI has a significant effect on the systolic blood pressure, keeping the age of the person constant. For her study, she collects a random sample of 125 patients from the city and estimates the following regression function: Y= 15.50 + 0..90B+1.15A. (0.55) (0 40) The test statistic of the study the student wants to conduct (Ho: B, = 0 vs. H, B, #0), keeping other variables constant is. (Round your answer to two decimal places.) At the 5% significance level, the student will ▼ the null hypothesis. Keeping BMIl constant, she now wants to test whether the age of a person (A) has no significant effect or a positive effect on the person's systolic blood pressure. So, the test statistic associated with the one-sided test the…
- one hundred adults who had their Type 1 or Type 2 diabetes were selected to determine if the inhalable version of insulin is able to manage blood sugar 'vels just as swell as injected insulin. The adults uses the inhaler for 3 months and then their blood sugar levels were recorded. Then they uses the injection for 3 months and then their blood sugar levels were also recorded. If we want to test if there is a difference in .average blood sugar levels using the two methods ?Which inference procedure should we use [Hint: test statistics ] None of these .A O Confidence interval about the population mean of the secondgroup .B O t-test about the difference between two means for independent samples CO t-test about the mean difference for paired samples .D O Confidence interval about the population mean of the first group .E OA researcher wanted to study the relationship between coffee drinking and heart problems. She interviewed all patients at several area hospitals and found that patients in the hospital for treatment of heart problems drank an average of 2.7 cups of coffee per day (Margin of error is 1.4 cups) while those patients being treated for other problems averaged only 1.4 cups of coffee per day (Margin of error is 0.8 cups). What conclusion can you draw about coffee as a cause of heart problems from this information?A) Coffee is bad for you.B) Coffee is good for you.C) Heart patients drink more coffee than other patients.D) None, because only patients in hospitals were interviewed.Does a high value of r2 imply that two variables are causally related? Explain.
- A researcher evaluated the effectiveness of relaxation training in reducing anxiety. One sample of anxiety ridden people received relaxation training, while a second sample did not. Then anxiety scores were measured for all subjects, using a standardized test. Us the information summarized in the following table to complete this item. The Effect of Relaxation Training on Anxiety Scores Group Mean Anxiety Score SE Control group 36 12 Relaxation training 18 10 What is the DV (remember, the DV is the data)? What is the level of measurement of the DV? What is the best graph to display this data? ExplainA diabetic person is interested in determining how the amount of aerobic exercise impacts his blood sugar. When blood sugar reaches 170 mg/dl, he goes out for a run at a pace of 10 minutes per mile. On different days, he runs different distances and measures his blood sugar after completing his run. The preferred blood sugar level is in the range of 80 to120 mg/dl. Levels that are too low or too high are extremely dangerous. The data generated are given in the following table: Distance (miles),x Blood sugar(mg/dl gram),y 2 136 2 146 2.5 131 2.5 125 3 120 3 116 3.5 104 3.5 95 4 85 4 94 4.5 83 4.5 75 Based on the scenario above, analyse the data with appropriate statistical methods and describe your findings in details. Use alpha=0.05 [note: use hypothesis, test statistics confidence interval etc.] ]If r = 0.5 and N = 4, would you conclude that a positive correlationexists between the two variables? Explain your answer. Whatif N = 500?