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Identify the type of observational study (cross-sectional, retrospective, prospective).A researcher from Johns Hopkins University obtains data about the effects of ...

Question

Identify the type of observational study (cross-sectional, retrospective, prospective).A researcher from Johns Hopkins University obtains data about the effects of alcohol on driving by examining car crash reports from the past five years.

Identify the type of observational study (cross-sectional, retrospective, prospective). A researcher from Johns Hopkins University obtains data about the effects of alcohol on driving by examining car crash reports from the past five years.



Answers

Researchers measured the blood alcohol concentration (BAC) of eight adult male subjects after rapid consumption of 30 mL of ethanol (corresponding to two standard alcoholic drinks).

The table shows the data they obtained by averaging the BAC (in mg/mL) of the eight men.

(a) Use the readings to sketch the graph of the BAC as a function of $ t $.
(b) Use your graph to describe how the effect of alcohol varies with time.

Was done with Chapter one. Just one more question to go and today will answer Computer that question. Seven. We're using data sets called alcohol, and it contains information on a sample of men in the United States to keep variables or self reported informant status called employees and alcohol abuse, along with many other variables. Right, So the main variables we keep track off is employed and abuse into both binary or indicators, dummy variables where you want to call them so they take only the values of zero and one. We don't want to take this for granted, so we're gonna describe or Davis said, and see what's going on. Indeed, we have a 9822 observations, 3300 lying variables and let's see, abuse indeed is a binary very boy, Balto one. If the person has reported two views out of a hole and the other one is employed right here, that was the one. If a person is employed or an equal desire of the persons on a boat in part A, we're being asked to find the percentage of the man in the sample that report abusing alcohol. So what do you need to do? It's account. First of all, how many of the binary variables are equal to one? It's 974 men have your boarding, abusing out of a hole. And in order to find the percentage of man and assembly for you using, we need to divide this number by the the number of men, which is equal to the total number of observations in this case, 9000 820. And if we do time to live, cable is two times 100 to get the right answer right away. It's 2 100 to 9.9 to 1% of men have reported abusing alcohol a little bit less than 10%. All right, next we're being asked, what is the employment rate? I assume this means that general employed women Great. So whatever you need to do is county the employees variable, is it? What's one? So this is a total number of men who have reported being employed, and we need to divide the number, and it ate to buy the total number of men. The sample multiplied by hundreds that would get 89.81 almost 90% off. Men are in fluid in the sample. In the general population, right? Without considering alcohol abuse or not, the employment rate is, uh, 89.81%. I know in part B. Consider the group of men who abuse alcohol. What is their employment? Great. Okay, now we need to have to calculate a ratio with, uh, the numerator will be the men who abuse on the whole end or employed, divided by the number of men would be is alcohol. So we have found the number of men who abuse alcohol is able to 974. Now, we need to count how many men abuse other hole. And this is a symbol for end and see the and our employees 100 and 50 and finally display, uh, 850 right 100 feet, divided by the total number of hold. These theories times 100. This gives us an employment rate of 87 0.26%. Let's say 87.3%. It's not that much different from the general employment rate, which is 89 81 now in part. See, we're being asked to find, uh what is the employment rate for the group of men who do not abuse alcohol. So we're gonna do exactly the same thing. But here, we're gonna change. The variable abuse from the search is gonna, um, look for the mine. A very believable to zero. So we're gonna do again Counties Musical zero. This is gonna be our denominator in the ratio. The total number of men we do not abuse alcohol. And now we need to find how many men, uh, did not abuse out the hole and their employees take this. Come on. That was going on here. Okay. All right. All right. Now we have It's simple ratio. Compute meeting for make it 100 90%. 9.1%. So 90.1% of known alcohol abusers are employed, compared to 87.3% um, for the alcohol abusers. So we're talking about a difference that is less than three per se. Okay. And hardy says, discuss the difference in your answers. Part two on B and C doesn't allow you to conclude that alcohol abuse causes unemployment. Well, uh, whenever you hear the war causes, your immediate reaction would mean no we literally can say anything about accusation here. First of all, because we have concluded a very, very, very elementary descriptive an analyst is whereas we need at make inference, willing to use inferential statistics or a kind of metrics to makes extradition predictions. But, um, even in that case, you know, in order to start suspecting that there might be something going on with alcohol abuse, we would need to see a difference in form and rates of maybe 2030 40%. And then maybe we would start, uh, you know, suspected that something is going on, but here, a difference of less than 3%. It's not only, uh, Major, you know, it doesn't really makes you suspect the other hallways uncle abuses housing anything. But we don't even know if it's statistically significant. So what? The very, very least, where we need to do is performs a test of sensitive that disco significance, which is a Standard T test and leftist Unova test, or maybe a multi varied regression analysis that takes into account very other love, many other characteristics off the man in the data set. And, um, unless we do that, we can say nothing about causation, and we don't even know that this difference is not, uh it is not because of some random samplings on random variations in the observations, or maybe because the data says no is not long enough to allow us to make accurate predictions.

In this question. We're collecting data from both male and female college students about binge drinking, and we're doing so through a survey. Once we get the data from the survey, we need to determine if we're going to be comparing the means or the proportions. In order to answer that question, we need to determine what type of information exactly we're collecting. We're going to be comparing means if we collect numerical data or quantitative data that we could actually calculate them enough. If we're going to be comparing proportions. It's because we have collected qualitative data, specifically binomial data such as a yes or no answer. In this case, if you go and serve a either a male or female college students, they're specifically going to answer. Yes, I have participated in Been Shrinking or no, I have not. So that would be a binomial, which means that we would be comparing proportions in this situation. The second question is what is the study design? There are two main types of study designs. There's experimental and observational experimental studies are studies in which you are manipulating a variable or several variables and determining the results of that manipulation are comparing the results of manipulating versus not manipulating, whereas an observation is specifically doing an observation and where you are not manipulating anything at all. In this case, we're not doing any manipulation. Yes, they are split into male and female categories, but they were already in those groups to begin with. We did not do the split there, so every single person was already either male or female. And we're simply asking and getting an observation of whether or not they do participate. So it is strictly observation in which we're going to then compare proportions.

Here we have questioned 50. It says the common definition of binge drinking. He's five or more drinks in one sitting for man or four more drinking's drinks in one scene. So a nontraditional study finds that students who binge drink have lower GPS and those who don't We're supposed to find some lurking variables that may confound, um, with intricate so variables that could affect G P A. That are not being accounted for. Just looking at great and binge drinking would be things like intelligence and study habits, which could affect your GP directly if you are maybe binge drink but also have great study habits. So you're passing your classes fine. Or, um, some people are just very intelligent and don't need to study as much. Can you spend more time playing? They could have a higher G p a. In the opposite. If you have really poor study habits or you don't naturally learns quickly, then that's gonna negatively affect your GP A. If you are been drinking, also factors I family income. Unfortunately, people who come from out of your families usually have, say, better study habits and excel more easily in school and one factor that wasn't necessary. Bitten in the guide book, I think it's also important is tolerance. It's possible that for, um, a man drinking five drinks, he actually we need quite few more in order for it to really negatively impact him, make him hit the level of drunk, which could, if he has a high times or she has a high tolerance, then they can get up the next morning and continue with their good study habits. And, um, do fucking the greats until a CZ I've been describing. This confounding can occur when there's other variables affecting grades. G P A. That are not being accounted for in the equations with skewing to some degree.

Question 50. He was looking up binge drink. So they look at people who claim that they do have been drinkable. Who don't your students, Um, and look at the GPS, and they include the people who do not who do been drink of a lower G p A. So if you drink, your GP is lower. If there's no drinking, you debate is higher. But, um, we cannot conclude this because they are looking variables. All our accounting for is drinking and greats. It's what alerted Variable is. It's It's a factor that states around and causes confounding. So at some mistakes isn't mistakes equation and that some part of the's individuals is not being explained. There could be other factors that impact the fact that their grades are down. One of the greats up that were not explaining that when we add the music creation could completely remove or even maybe strengthen what we're seeing. So a few of these are just general intelligence. Individuals just learn faster than others. They're gonna have higher creed, so it doesn't matter if they drink or now they're gonna have a hard creates also income of your parents. Socioeconomic status does Chorley. Um, with Intel there success educate education wise, I would say, Um, that's what. Also, if your parents have money, they can pay for actual activities tutors, etcetera, which could increase your grades regardless of your bringing status and only studying habits. Some individuals might binge drink, but, um, study wall on that is that they don't and actually do better than individuals who don't been string but do not have a good health. So these are just three examples off looking variables that can impact GP A. Therefore, it doesn't have anything, doesn't act on drinking and under King and suddenly ex Drexel on the outcome that need to be kept into the equation or is considered when drawing conclusions.


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