6. How safe are anesthetics? (3.1, 3.6) The National Halothane Study was a majorinvestigation of the safety of anesthetics. Performed in 34 major hospitals, the studyshowed the following death rates for four common anesthetics:AnestheticDeath rateA1.7%B1.7%C3.4%D1.9%There seems to be a clear association between the anesthetic used and the death rateof patients. Anesthetic C appears to be more dangerous.104A) Explain why we call the National Halothane Study an observational studyrather than an experiment, even though it compared the results of using differentanesthetics in actual surgery.B) When the study looked at other variables that are related to a doctor's choiceof anesthetic, it found that Anesthetic C was not causing extra deaths. Explain theconcept of confounding in this context and identify a variable that might beconfounded with the doctor's choice of anesthetic.

Introduction: The study involves assessing the association between the doctor's choice of anesthetic…

Answered: 6. How safe are anesthetics? (3.1, 3.6)…

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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ie 19. A certain drug is claimed to be effective in curing colds. In an experiment on 164 people with cold, half of them were given the drug and half of them given sugar pills. The patient's reactions to the treatment are recorded in the following table : Helped Harmed No effect Total 52 10 20 82 Drug 44 12 26 82 Sugar pills Total 96 22 46 164 On the basis of this data, can it be concluded that there is significant difference in the effect cs the drug and sugar pills ? (For v = 2 x0os = 5.99) 0.05
An experiment was designed to study oil additives that could reduce polluting the air. Two additives were considered in the study. The two additives X1 and X2 were controlled and the level of the pollution Y is observed. The data were as follows: Y X1 X2 3.9 1.5 2.2 7.5 1.5 4.5 4.4 1.7 2.2 8.7 1.8 4.4 9.6 5.5 4.3 8.5 5.5 4.5 Find the regression equation Is the model valid? Which independent variable is linearly related to Y?
What test do I need to run?
The following data are from a repeated-measures study comparing two treatment conditions. Complete the table Treatment Person I II Totals Differences (II – I) A 11 13 P = B 8 7 P = C 10 13 P = D 8 8 P = E 7 13 P = F 10 12 P = M = M = N = MDD = T = T = G = ∑D = SS = SS = ∑X² = SSDD =
ed weight (in kg) and total serum cholesterol (TSC in mg/dl) data for five men (n = 5). They tested for association between weight and TSC at 5% level of significance. weight, X TSC, Y X*X Y*Y X*Y 37 2.9 1369 8.41 107.3 50 0.7 2500 0.49 35.0 67 3.3 4489 10.89 221.1 70 4.2 4900 17.64 294.0 57 3.8 3249 14.44 216.6 SUM: 281 14.9 16507 51.87 874.0 What are the Null and Alternate hypotheses for this test? Clearly label your answers as HỌ or H1. (Do not use a numerical format. Both of your statements must be in sentence form, and say something about the weight
For the following data 4,4,6, 10 o = 2.4 Then C.V.= Select one: O a. 25% O b. 47% Ос. 22.4% d. 40%
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 ## ##…
3
6
1. Effect size and Cohen's D: a. What is an effect size? What info does it tell you, when is it calculated, etc.? b. What is Cohen’s d? What info does it tell you about the independent variable and dependent variable? (think of how you write the sentences explaining your numbers)
The director of student services at Oxnard College is interested in whether women are less likely to attend orientation than men before they begin their coursework. A random sample of freshmen at Oxnard College were asked what their gender is and whether they attended orientation. The results of the survey are shown below: Data for Gender vs. Orientation Attendance Women Men Yes 338 No 317 349 287 What can be concluded at the a= 0.10 level of significance? For this study, we should use z-test for the difference between two population proportions a. The null and alternative hypotheses would be: Ho: p1 p2 (please enter a decimal and note that p1 and μl represent the proportion and mean for women and p2 and 2 represent the proportion and mean for men.)
Q3, just parts d, e, f. (posted a, b, c as a different question)

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