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Question 7 (1 point) Researchers at an epidemiology clinic are interested in the difference in the incidence of a number of severe adverse events that occur during ...

Question

Question 7 (1 point) Researchers at an epidemiology clinic are interested in the difference in the incidence of a number of severe adverse events that occur during clinical trial between the control and treatment groups. Suppose the following table illustrates the incidences for the most common SAE reported in the population, severe nausea, reported over the course of the 10 year intervention: Total Participants Reporting Severe Nausea Total Participants Control 267 1789 Treatment 485 1024Calcul

Question 7 (1 point) Researchers at an epidemiology clinic are interested in the difference in the incidence of a number of severe adverse events that occur during clinical trial between the control and treatment groups. Suppose the following table illustrates the incidences for the most common SAE reported in the population, severe nausea, reported over the course of the 10 year intervention: Total Participants Reporting Severe Nausea Total Participants Control 267 1789 Treatment 485 1024 Calculate incidence of severe nausea among the treatment group: 474 per 1000 persons followup 354 per 1000 persons followup 149 per 10O0 persons followup 267 per 1000 persons followup



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Match each type of epidemiology study with its description. A. examination of past case histories and medical test results conducted on patients in an outbreak B. examination of current case histories, interviews with patients and their contacts, interpretation of medical test results; frequently conducted while outbreak is still in progress C. use of a set of test subjects (human or animal) and control subjects that are treated the same as the test subjects except for the specific treatment being studied D. observing groups of individuals to look for associations with disease E. a comparison of a cohort of individuals through the course of the study
experimental analytical prospective descriptive retrospective

In here wants us to identify the following items if possible for the particle er problem in this particular case. So for a here, it's asking for the population. So in this particular case, we know that they're studying us adults, so that's gonna be our population. So us adults here for be here. It asked for the population parameter of interest. So essentially, what I'm asking for is what they're studying in this particular case. So, um, in this particular case, they're looking for alternative, um, medical treatments here for part C here. Asked us for assembling for him to sampling for him is the method through which they conducted it. In his particular case, we aren't known what we are told exactly what they are. So this is gonna be not applicable for D here. The sample itself, the sample itself here is going to be subscribers of the Consumers Union who replied for me here. It asks us the sampling method. So in this particular case, this is going to be a convenience sample. Due to the fact that the sample is most likely got in from, um, surveys random surveys through which their customers, um, are given and part of here ass us for any particular problems or sources of bias. So this is gonna be first of all under coverage, as we don't know, um or were not given a set amount of a publish in that we can make representative of what we're trying to look for. And non response bias also occurs due to the fact that this is not a survey through which people actually go out of their way to go to. However, this is just based on random sending through various surveys that are given after a particular service.

In this problem, we're going to be considering data from the Centers for Disease Control to determine health risk behaviors among college students. And in this survey, college students were asked how often the war a seat belt when riding a car driven by someone else. And so we have different responses and different frequencies. So in the first part of the question, we're going to be constructing a relative frequency distribution. Now for relative frequency distribution, we want to introduce a new column that would be for the relative frequency. And here the relative frequency compares each frequency to the total frequency. So we want, first of all to get the sum of frequencies. And and is that from your assumption? And we see that the total is 4776. Next we get the value of frequency for each category divided by the total frequency which is 4700 two. Be that formula all the way down. So now we have the different frequencies, the different relative frequencies for each category. Yeah, next. In part B. We want to get what percentage of respondents answered always. So we focus on the category always. And that is a rich portion of 0.5 272 And as a percent, this will be 52 0.72%. So you can say that 52.72% of the respondents answered always. Which is actually the greatest number in Patsy. We're going to get the percentage of respondents who answered never or really. That means we would have to get the total for the two categories. Never and really? And when you sum this to up, you get zero point zero 94 there's a percentage. This is going to be 9.4%. So 9.4% of the respondents answered never or rarely. In part D. Of the problem. We're going to be constructing a frequency bar graph. So a frequency biograph would be obtained by choosing the fast two columns, the response column and the frequency column. Once you've selected it we press in such and then we go to chart and then we insert a column or batch at. So the first one is what we need. And this is a frequency biograph for the data. Next in part this is party in part E. We want to get relative frequency bar graph for that. We shall select the column for response and the column for relative frequency. And then we insert a bar chart. So the press of the batch at the first one which is the two D. And this is our relative frequency bar graph. But next in part F. We want to construct a pie chart. So for a pie chart we could use the first two columns the response of the frequency. Then you can start and then you go to charts and select the type of pie chart you wish here with electing the two D. Pie chart which shows us the frequency and the slices for different categories. Soon that's part F. And you can see the biggest chat is for always those who always wear their signals. Now in part G. We're going to suppose that a representative from the C. D. C. Says that 52.7% of all college students where are seat belts and then tell whether this statement is descriptive or inferential. So a statement such as 52.7% of college um The college students were built can be made because when we check these results from the have relative frequency um distribution. We see that those students who were about who were built are actually 52.72%. And since we're using the summaries from from the data to make such a statement when that statement is going to be a descriptive statement and not an inferential statement.

Okay, so we can go ahead and read out Arnel Apple Icis. It's not Which is simply that P one is equal to P two. And our alternative responses which is P one will be less than two. Now we can go ahead and catholic the sample proportions. Yeah, Some sample portion one. It's simply going to be excellent over and run Which is 642 over 2105 or 0.305. As for P two will be X two over end to which will be 697 over 2115 Which will be 0.32 six enough of pool proportion. Um It simply can be X one plus X two Voter and one plus 2 Which will give us zero three 73 Now for the test statistic scene, Yeah, Some TP one speak to oh there. The square root. Yes. Mhm. Yeah. And his p times square number and Plus one over and to So if you go ahead and plug in all those values, we'll get negative 1.72 for RSC statistics. So since you know that the critical mhm value corresponding to probability of alpha. Yeah. She because you have five will be -1.645. And we know that negative 1.72 is less than negative 1.645. We can therefore reject. Do you know about this? Yeah. No. For part B. The difference in sample proportions is difference Is less than 0.02. So therefore this difference will not be practically significant.


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