A 1-1 matched case-control study was conducted among office workers on the association betweensuffering chronic lower back pain and sitting at a PC. There were 118 cases (suffering from backpain), individually matched to controls (not suffering from back pain) on sex, age, and generalexercise habits. The exposure was the amount of time spent at a PC. The data are in Table 1:Case> 4 hours/day<4 hours/dayTable 1Controls> 4 hours/day1813<4 hours/day2562Use a suitable test to test for no association between suffering chronic lower back pain andtime spent sitting at a PC.

The dataset is given as- Controls ≥4 hours/day <4 hours per day case ≥4…

Answered: A 1-1 matched case-control study was…

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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It is a 2 part question. How can we find normality?
According to a dietary study. high sodium in take may be related to ucers. stomach cancer. and migraine headaches. The human requirement for salt is only 220 milligrams per day. which is surpassed in most single servings of ready-to-eat cereals. If a random sample of 20 similar servings of a certain cereal has a mean sodium content of 244 milligrams and a standard devlation of 24.5 miligrams, does this suggest at 0.05 level of significance that the average sodlum content for a single serving of such cereal is greater than 220 milligrams? The p-value of the test statistic in 6 decimal places and the critical value in two decimal places is: example answer: 0.123456 and 1.23
An epidemiologist found five cases of “big toe cancer” in the Yukon Territory. Because there were only a few cases, the epidemiologist decided to conduct a matched case-control study to determine whether shoe size larger than 9 is a risk factor for big toe cancer. Cases were individually matched to one control for daily activity, history of athlete’s foot, and history of ingrown toenails. The following data were gathered: Shoe size > 9 Pair Case Control 1 Yes No 2 No No 3 No Yes 4 Yes Yes 5 No Yes Compute the proper measure of association. Interpret your results. If you were to investigate a rare cancer in Lynchburg, where might you look for data? What would be necessary legally and ethically to be able to utilize this data set(s)? Submit your thread by 11:59 p.m. (ET) on Thursday of Module/Week 3, and submit your replies by 11:59 p.m. (ET) on Sunday of the same module/week. 1
Researchers conducted a study to determine the effects of different types of alcohol on the peak alcohol concentration. In one part of the study, the researchers gave 15 randomly select males a controlled volume of vodka and monitored the subjects' alcohol concentration following the period of consumption. The legal limit for driving is 80 mg/dL (milligrams per deciliter of blood). A hypothesis test was conducted to see if the mean peak alcohol concentration from drinking vodka was different from the legal driving limit. This was reflected in the null and alternative hypotheses ?0:??1:?=80 mg/dL≠80 mg/dL The researchers required their results to be statistically significant at a level of ?=0.10. The mean peak alcohol concentration of the participants after drinking a controlled volume of vodka was 77.4 mg/dL with a standard deviation of 17.25 mg/dL. Determine the confidence interval that corresponds to the ?‑test. Give the lower and upper bounds precise to two decimal places
In a One-way Between Subject ANOVA, the number of levels the IV had was 3, and the within/error degrees of freedom was 48. What was the total number of people in the participants analyzed in the study
Attractiveness of body types has been a large discussion relating to effects on youth and culture. Unhealthy levels of BMI are often associated with beauty. A researcher decided to study how young heterosexual adults body type preferences related to BMI. Participants were asked to use a computer program to design their desired partner. The program then calculated the BMI of the designed partners. The table summarizes the results based on a SRS of 35 men and 48 women. BMI designed by men n=35 x-bar=18.850 stdev=1.750 SE Mean 0.277 BMI designed by women n=48 x-bar=25.860 stdev=4.215 SE Mean 0.625 Use this information to conduct a test to decide if male and/or female body type preferences are associated with healthy BMI measurements. You should have two complete tests here. You may assume the populations are normally distributed.
The leader of two postpartum women’s support groups is interested in the depression levels of the women in her groups. She administers the Center for Epidemiologic Studies Depression Scale (CES-D) screening test to the members of her groups. The CES-D is a 20-question self-test that measures depressive feelings and behaviors during the previous week. The mean depression level from the screening test for the 10 women in the first group is μ₁ = 16; the mean depression level for the 14 women in the second group is μ₂ = 10. Without calculating the weighted mean for the combined group, you know that the weighted mean is:
A substance abuse counselor wants to demonstrate the effect of situational stress on alcohol cravings. He recruits two groups of men who are similar in respect to history of alcohol use and demographic variables. He divides them in to two groups. In one group(n=11), the men are exposed to a stressful situation and then asked to complete a measure rating their alcohol cravings on a scale from 0-10, where 0 representsno cravings and 10 represents intense cravings. In the second group (n=10), the men are exposed to a neutral situation and asked to complete the same measure. What test and graph should I create to find out if a stressful situation result in more intense alcohol cravings than a non-stressful situation?
A graduate student is interested in how viewing different types of scenes affects working memory. For his study, he selects a random sample of 36 adults. The subjects complete a series of working memory tests before and after walking in an urban setting. Before the walk, the mean score on the test of working memory was 9.1. After the walk, the mean score was 1.4 higher. The graduate student has no presupposed assumptions about how viewing different types of scenes affects working memory, so he formulates the null and alternative hypotheses as: H00 : μDD = 0 H11 : μDD ≠ 0 Assume that the data satisfy all of the required assumptions for a repeated-measures t test. The graduate student calculates the following statistics for his hypothesis test: Mean difference (MDD) 1.4 Estimated population standard deviation of the differences (s) 1.6 Estimated standard error of the mean differences (sMDMD) 0.2667 Degrees of freedom (df) 35 The t statistic 5.25 The critical values of t…
When a t-test is used to compare pre- and post-treatment data. What does the t-test reveal about the difference between baseline and treatment?
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.
Part 1 of 4 A doctor in Oklahoma City wants to know whether the average life span for heart disease patients at four hospitals in the city differ. The data below represents the life span, in years, of heart disease patients from each hospital. Perform an ANOVA test with a 10% level of significance to test whether the average life span of heart disease patients in Oklahoma City differs depending on the hospital that treats them Life Span of Patients Treated at Hospital 1: 8.1, 1.2, 7, 11.5, 21, 2, 15.3, 19.2, 10.5, 15.4, 12.7, 15.3, 12.1, 7.5, 11.4, 16.4, 26.7, 14.6, 1.5, 16.3, 12.6, 0.8, 18.2, 4.2, 9.6, 21, 16.3, 2.7 Life Span of Patients Treated at Hospital 2: 17.6, 11.6, 16.8, 5.2, 6.7, 3.2, 13.8, 12.5, 0.9, 6, 14.3, 1.8, 14.8, 10, 5.8, 15.2, 10, 3.7, 11.4, 21.6, 12.9, 0.5, 9.2, 13.9, 10.9 Life Span of Patients Treated at Hospital 3: 8.5, 2.3, 11, 7.4, 14.8, 5.8, 11, 3.4, 10.9, 1.1, 5.9, 21.6, 12.5, 0.1, 15.5, 15.4, 0.8, 7.7, 5.6, 12, 7.1 Life Span of Patients Treated at Hospital 4:…

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