Problem #3: (a) Erythromycin is a drug that has been proposed to possibly lower the risk of premature delivery. A related areaof interest is its association with the incidence of side effects during pregnancy. Assume that 30% of allpregnant women complain of nausea between the 24th and 28th week of pregnancy. Furthermore, supposethat of 175 women who are taking erythromycin regularly during this period, 64 complain of nausea. Find thep-value for testing the hypothesis that incidence rate of nausea for the erythromycin group is greater than for atypical pregnant woman.

Answer Given that: p=30% =30/100 = 0.30 X =64 n =175 proportion =x/n =64/175 ~0.3657 right tailed…

Answered: (a) Erythromycin is a drug that has…

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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16
A common idea is that people can temporarily postponed death to survive a major holiday or important event. A study found that there were 6907 deaths before Thanksgiving and 5739 deaths after Thanksgiving. Test the claim at the 0.05 significance level that the proportion of deaths in the week before Thanksgiving is less that 0.5. Based on your result, does it appear that peole can temporarily postpone death to survive the Thanksgiving holiday?
imagine a large class where nearly everyone scores between 83.84%, with hardly any dispersion beyond this narrow range (so it would appear to have a very narrow peak). How would your describe this distribution of data in terms of kurtosis?
Data originally from DASL http://lib.stat.cmu.edu/DASL/Datafiles/CancerSurvival.html (Links to an external site.). Some bronchial cancer patients had the following survival times (in days) after receiving a certain treatment: 20, 37, 63, 64, 72, 81, 138, 151, 155, 166, 166, 223, 245, 246, 450, 459. (The second instance of “166” is not a mistake.) Do these numbers suggest that the average survival time, for all bronchial cancer patients who receive that treatment, is significantly different from 200 days? CANCER SURVIVAL Report an appropriate one-sample hypothesis test and use a 10% significance level. For Step 4 of the six-step process that was taught in this class, choose the BEST option to complete the following sentence: We assume that the sample of subjects is a SRS and we assume that the population of observations has no outliers ... and is Normally distributed. and is without a doubt bell-shaped. and is Uniformly distributed. (nothing needs to go here because the sample…
first picture is the background information
Data originally from DASL http://lib.stat.cmu.edu/DASL/Datafiles/CancerSurvival.html (Links to an external site.). Some bronchial cancer patients had the following survival times (in days) after receiving a certain treatment: 20, 37, 63, 64, 72, 81, 138, 151, 155, 166, 166, 223, 245, 246, 450, 459. (The second instance of “166” is not a mistake.) Do these numbers suggest that the average survival time, for all bronchial cancer patients who receive that treatment, is significantly different from 200 days? CANCER SURVIVAL Report an appropriate one-sample hypothesis test and use a 10% significance level. For Step 5 of the six-step process that was taught in this class, which would be the appropriate procedure and why? Choose the correct option. Group of answer choices We would do a t-procedure because we have the standard deviation. We would do a t-procedure because the sample size is large. We would do a t-procedure because we do not have the population standard deviation and…
first picture is the background information
An elephant eats an average of 3 bushels of alfalfa per day, with a standarddeviation of 0.8 bushels. Suppose that you need to feed 10 elephants for oneweek. If the distribution is normal, what is the minimum number of bushels ofalfalfa so that there is no more than a 10% chance of running out by the end of the week?
Diabetes Physicians recommend that children with type-I (insulin dependent) diabetes keep up with their insulin shots to minimize the chance of long-term complications. In addition, some diabetes researchers have observed that growth rate of weight during adolescence among diabetic patients is affected by level of compliance with insulin therapy. Suppose 12-year-old type-I diabetic boys who comply with their insulin shots have a weight gain over 1 year that is normally distributed, with mean = 13 lbs and variance = 13 lbs. (Assume for parts (a) and (b) that weight can be measured exactly and no continuity correction is necessary. Round your answers to four decimal places.) USE SALT (a) What is the probability that compliant type-I diabetic 12 year-old boys will gain at least 17 lbs over 1 year? X (b) Conversely, 12-year-old type-I diabetic boys who do not take their insulin shots have a weight gain over 1 year that normally distributed with mean = 7 lbs and variance = 13 lbs. Answer…
Do test scores at pre-treatment differ from test scores at post-treatment? Note, this analysis should be conducted ignoring the treatment group they are in. Do male and female subjects differ on their pre-test score performance? Knowing the number of hours the student studied for the exam, can you predict their post-test scores? Is there a significant relationship between subject’s IQ and pre-test scores? Do the three treatments differ significantly from one another at pre-test? Do student IQ scores differ significantly from the population (μ = 100 & σ = 15)? Create your own research question based on the data. (All analyses are to be tested at α =.05, two tailed)
If a treatment is expected to decrease scores in a population with µ= 30, then the alternative hypothesis is µ ≤ 30. True or false?
first picture is the background information

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