In a clinical trial to test whether a new drug (treatment) reduces the risk of stroke, the resultsobserved in N=260 subjects is reported below.ObservedTreatment GroupStroke (S = 1)No Stroke (S=0)TotalTreatment (I=1)27108135Placebo (T=0)13112125Total40220260ExpectedTreatment GroupStroke (S = 1)No Stroke (S=0)TotalTreatment (T=1)135Placebo (T=0)125Total40220260Chi-Square CalculationTreatment GroupStroke (S = 1)No Stroke (S=0)Treatment (T=1)Placebo (T=0)Chi-Square4.595

We want to find the expected frequency

Answered: In a clinical trial to test whether a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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You think that there might be a relationship between stress for Middle Schoolers and the number of after-school activities that the student participates in. Conduct an ANOVA with an 8-step hypothesis on the following data to find if there if there is a significant relationship occurring. # of after school activities Stress Scores 0 1 0 2 0 8 1-2 3 1-2 10 1-2 4 1-2 2 1-2 6 3 or more 9 3 or more 8 3 or more 3
Left ventricular mass (LVM) is an important risk factor for subsequent cardiovascular disease. A study is proposed to assess the relationship between childhood blood-pressure levels and LVM in children as determined from echocardiograms. The goal is to stratify children into a normal bp group (< 90th percentile for their age, gender, and height) and an elevated bp group (≥ 90th percentile for their age, gender, and height) and compare change in LVM between the two groups. Before this can be done, one needs to demonstrate that LVM actually changes in children over a 4-year period. To help plan the main study, a pilot study is conducted where echocardiograms are obtained from 10 random children from the Bogalusa Heart Study at baseline and after 4 years of follow-up. The data are given in Table 1 . Table 1 Pilot data on left ventricular mass (LVM) in children from the Bogalusa Heart Study ID Baseline LVM (g) 4- year LVM (g) Change (g)* 1 139 163 24 2 134 126 -8 3 86 142 56…
Researchers investigate how the presence of cell phones influence the quality of human interaction. Subjects are randomly selected from a population and divided into an experimental group that is asked to leave their phones in the front of the room and a control group that are not asked to leave their cell phones at the front of the room. Subjects are left alone for 10 minutes and then asked to take a survey designed to measure quality of interactions they had with others in the experiment. What statistical test is appropriate?
Taxi Brand A Brand B1 38,300 39,8002 37,700 38,1003 42,200 43,0004 42,300 41,6005 48,200 47,0006 36,100 40,4007 35,300 36,4008 44,600 45,900
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Can eating a yogurt a day cause people to lose weight? In a study investigating this: (1) What is the explanatory variable? (2) What is the response variable?
Which best illustrates the distinction between statistical significance and practical importance? Multiple Choice "This year, 360 of 440 statistics students at Oxnard Technical College rented their textbooks, compared with 110 of 330 students last year. This is a significant increase." "Our new manufacturing technique has increased the life of the 80 GB USB AsimoDrive external hard disk significantly, from 240,000 hours to 250,000 hours." "In 50,000 births, the new vaccine reduced the incidence of infant mortality in Morrovia significantly from 14.2 deaths per 1000 births to 10.3 deaths per 1000 births." "The new Sky Penetrator IV business jet’s cruising range has increased significantly from 3,975 miles to 4,000 miles."
A health officer thinks that there is an association between diabetes (DM) and hypertension (HPT). He believes that those with DM are more likely to have HPT as well. For his research, from the hospital records, he selected a random sample of 400 patients, 300 with DM and 100 without DM. Out of the 300 DM patients, 60 had HPT as well and out of the 100 non DM patients 10 had HPT. He also recorded the patients’ gender. With the data, he performed two analyses, one for all policyholders and the other by gender. The following are some of the output from SPSS. Must the manager consider gender as well in this case? If yes, stating the evidence, explain why. If you are the health officer, how would the results above help you in making decision? What other variables, if any, should be considered as well?

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