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38 - Suppose data mining is used to determine whether or not a customer would purchase a hybrid vehicle: In data mining this is referred to as what type of problem?...

Question

38 - Suppose data mining is used to determine whether or not a customer would purchase a hybrid vehicle: In data mining this is referred to as what type of problem?Regression. Transactional, Unsupervised. Classification; None of the above_ Bos birak

38 - Suppose data mining is used to determine whether or not a customer would purchase a hybrid vehicle: In data mining this is referred to as what type of problem? Regression. Transactional, Unsupervised. Classification; None of the above_ Bos birak



Answers

Identify which of these types of sampling is used: random, systematic, convenience, stratified, or cluster. A student of the author conducted a survey on driving habits by randomly selecting three different classes and surveying all of the students as they left those classes.

This question is back looking at disk drives from a previous question, and I've done a sketch of what the pot looks like. A scatter part of the residuals from the regression. So we asked if there are any assumptions or conditions that violated. So you got the report. Remember the conditions that could be violated? Linear heresy. Equal spread. I'm finally out. Plus and looking at this clock Weaken City, this point head is my old away from a Lamar other points. So I would say that point is definitely an outline. And if we look at Linea Aris E, there's no other shape, really is no curves or even though it's week or so that you could have a linear trend that looks a little bit maybe like that. So even though it's no completely accurate, you can see that it almost follows that line in a very big way. So I would say we do have many aridity, an equal spread. Well, if you look at the points, there are boy spread about. We have this little group here, so you could argue that the spread isn't completely equal, but I would definitely say it's no unequal enough to say that that is violated. So the bones of a is to say there are out lies. It then asks what you'd recommend to do for this regression. So while I was at less Andi, part B is what would you do on that lot Now the others. This one is quite simple in that you remove the our liar from the data on this is to get rid of that condition.

So in this problem, we're looking at auto mileage, and we're looking at what the average mile per gallon is for all new hybrid small cars. And we're going to use consumer reports in a random sample of such vehicles, which gives an average of 35.7 MPG. So we want to identify the variable. The variable is what is being measured. So in this case, it is the average MPG. No. Yeah, yeah. And again, the variable is what is the thing of interest that the researchers are studying? And then Part B is asking if the variable is qualitative or quantitative, and in this case, it is quantitative because it's a number, Um, qualitative would be, um, like the color of the car or something like that. But this is a number. So its quantitative Mhm. Yeah. Okay. Since it will be like 35.7 example, um, for the average, then for part C, we want to, uh, find the implied population. So this is who is being studied in this case? It's all new hybrid small cars so we can see the difference between a population and a variable so the population or the individual is who is being started. And the variable is what is being studied. Uh, but in this case, the population is just the hybrid small cars. Yeah, yeah.

Question 36 provides information on model year 2009 motor vehicles, and I've reproduced just a couple of rows of the table, which is sufficient to discuss how to answer the question. So part, they asked, What are the individual is in this data set, and the individuals are actually the model year 2009 motor vehicles so we can say 2009 motor vehicles and then for Part B were asked what variables are measured? And are they categorical or quantitative? So the headings are actually the variable is measured, and so making motto is categorical. So it's just the name and brand and year for the name and model of the vehicle. Vehicle type is categorical. Categorical categories are usually words or qualitative descriptions, so subcompact lard, transmission type, automatic or manual. That's also categorical number of cylinders. That's at that a numerical value that is a quantity. So that's quantitative city mpg again, that's quantitative value and highway mpg is quantitative

Everyone today, we're going through another problem from chapter one of your textbook. And in this problem, we are again a set of four different questions will have a or C and finally, and, um, we're asked to identify whether or not these questions yields categorical data results or quantitative. So, in part A, they asked, what price did you pay for a vehicle? Um, another way to think about this is how many dollars do you have to spend to cut the vehicle? Someone you have? How many of something involved, you know, dollars. In this case, it's going to be miracle value. And it's going to be t that The first question is concentrated. All right. And the second question, your ass, How did you pay for the view vehicle and their three options given cash least or find it, Um, when options are getting like these and they're not miracle, it's always gonna be credible because you know the method of payment itself when you have different methods. You something about something Um, like you could cash in after the recent federal finance method, it's gonna be counted because those muffins are split up and psychotic. Three different words. All right, And part. See, you're but you're asked, how likely would you recommend this vehicle to a friend? Um, and they give you options for different options from definitely not there. Probably not, too. Probably wrote to definitely will. When they give you four options like I'm interested Party. It's always gonna be categorical, especially in this case. It's like, How likely would you recommend very opinion based questions like this often tend to be categorical unit. They have numbers. So in party, like I just mentioned before, it's asked for your overall rating from on a 10 point scale. But don't get confused just because it's a 10 point scale on your numbers. Um, there is that finite end. See breaking things that 1 to 10 about it of, um, the vehicle itself and when you are ranking from 1 to 10 ten one is separate category from 23456 70 intact. But then those air your turn categories, so there's a finite number of categories. It's not like they're just like on a scale this specifically say it's a 10 point scale, and like I said before it, categorical data can still be miracle in nature so long as it represents, You know, so long as like it was with this question, its opinion based again, um, and it has numbers, but it's still opinion based, and it has a finite end to its numbers. So you would have 10 different categories for this particular, um, question. You have to have it away for one category for choose had it for three categories before category five all the way up to. And there you have it. If you guys enjoy this video, please of the like right next to it. Thank you for watching.


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