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Consider the following summary of a Pew Research Center study about how much U.S. adults believe global clirnate change is affecting their corununity:SomeNot Too Mu...

Question

Consider the following summary of a Pew Research Center study about how much U.S. adults believe global clirnate change is affecting their corununity:SomeNot Too MuchGreat DealNc AnsterHow Muci Ciimare Cnange Affects Loca Cummuninpoints) Which type of graphs is this?points) The variable displayed here is the opinion of U.S_ adults the percent of U.S: adults with different opinions whether U.S adults believe global climate change is affecting their community the number of US_ adults believe globa

Consider the following summary of a Pew Research Center study about how much U.S. adults believe global clirnate change is affecting their corununity: Some Not Too Much Great Deal Nc Anster How Muci Ciimare Cnange Affects Loca Cummunin points) Which type of graphs is this? points) The variable displayed here is the opinion of U.S_ adults the percent of U.S: adults with different opinions whether U.S adults believe global climate change is affecting their community the number of US_ adults believe global climate change is affecting their community None of the above



Answers

The Pew Research Center for the People and the Press (http://people-press.org) has asked a representative sample of U.S. adults about global warming, repeating the question over time. In October 2010, the responses reflected a decreased belief that global warming is real and due to human activity. Here’s a display of the percentages of respondents choosing each of the major alternatives offered:

(Pie Chart Can't Copy)

List the errors in this display.

In question 17. We're going to be looking at the errors found in this pie charts and, well, as you look at it, it looks very appealing to the eye because it's three dimensional. But the fact that it is three dimensional and not just a suckle makes it violate the area principle. So the fast era is that it by a lit the area principle. When three dimensional ships are used as opposed to the two dimensional ships, it makes it more difficult to compare fractions of the whole, and therefore it distorts the signs off each slice. The second error that we notice in this patch it is that all the category tussles don't add up to 100%. So when you take 18 plus nine plus 32 plus 24 the total is 93% which is a nera. So the second era is that the slices total. He's not 100%. Then that era that you notice is that thesis. My church has no title, so 1 may not be able to understand the information that the fracture is supposed to display

So how do we know that climate change is happening? And that's human induced? I think it's important thing about what science is and how scientists come up with knowledge and then what scientific support there is for climate change. In this chapter, they talked about Green House gases, but there's other scientific support that you go to and look at the evidence backing up the information that the scientists are giving us about climate change.

Okay for this problem were given some information or context of for young Americans 17 to 20 year olds. How much they're willing to pay for an environmentally friendly car reported in the USA Today. And I'm gonna preview start steps. They're going to be the kind of name the variables, uh, identify what kind of variable it is, and then show a couple different types of graphs. So, as you can see, I have, ah, kind of put up an apple it here. That is really good for doing a lot of different types of graphs. It's called stap lit. Um, and this is a one categorical variables impact for part B. I had to answer that question. I'll write it out in a second, but with the Neymar variable of interest. And we have to talk about the type of care of variable. So this is a categorical categories of of choices in this case, choices of how much they would be willing to spend on it. Environmentally friendly car. So let's drop without first. So So this is the percent of young adults, specifically kind of long answer here, but more detailed percent of 17 to 20 year olds willing to pay more foreign Obama. Really, really car. A long answer. But, Willa, that indoor park may early is my copy paste technique. Just make sure we about nice, detailed answer there for a party. Um, say that there. Right. So that's when you're creating a, um ah, categorical variable. So you have all these different category names in this case, the names and you kind of the hint is just kind of words. What? They are in this case. So, um, this is laid out into a lot more. Okay, so they told us that 11% will be willing to pay a lot more. Okay, Um, the category was based on a survey somewhat more. And that was 36 and the third was said they'd pay a little bit more for environmentally friendly car. Infinitely, there was responses that so they would not be more. They didn't even work for environmentally friendly car. And 20% of the respondents said that the young adults Okay, so if using stop, Let me do this by hand. If you do it by hand and you into a pie chart, you need to kind of lay this out and look at 360 degrees and find out the number of, you know, angles the degree of the angles to do that by hand. Um, I'm gonna do it for time wise. I'm gonna do it using this apple. It okay? And I was my default ends up being a bar chart. This problem actually asks for both of these things, but just to go in the order, they asked for it. Um, there's a nice scrap distribution, and I tell my students may be used technology to make sense and get a hint. Um, it's good to do a couple by hand, too. So just to keep track of the data here, I'm going. Teoh snapped this and that kind of did it ahead of time is a backup plan, but part c said they construct construct a pie chart. Some kind of copy this in while I have it now improve what's cut off there at the end. All right, so there is that one, and this is a nice problem. I like the way these are asked to, because it's is to kind of compare and contrast. Uh, how these different types of graphs So what's nice about you since Apple it to, um you can just kind of change this to instead of showing the pie chart, you can. Since it is categorical data, you can just make it a bar chart. All right, So paste that into and I will, uh, include the numbers at the bottom. So these are really part c purty screen bigger since we have all the information here. So there's most of what we have. So to take it from the top of the little improvement in the labeling here, So party Ask what the variable of interests and interest is. Environment friendly cars with the variable is the young adults would purchase the cars is true. Variable category of how much they cared about it and parties that identify the type of variable. So this is a categorical conservative categories. So categorical will have us doing these checks of graphs. Categories in this case are percentages, actually, actually, percents of how much more it looks like somewhat more is kind of the winner. In this case, you can tell by how tall the bar graph is there and how big that sector of the pie graph pie chart is there? Okay, so apart. See, was this and be Let's see, actually, you see? And then d was the bar chart just for labelling. There's be and, um, they had it down there at a time. So there's all of our answers. I'm gonna just stroll up a little bit so you can see all the number is there, Um, and we will answer part e together now sometimes is a little subjective, but a big problem learning statistics. You do want to kind of say, which is the better graph? I'm going to go with Part E. I'm going to say that the pie chart is better. And the reason why is because when you have parts of holes percents out of 100 I can visually see clearly this light blue, the somewhat more is the winner. He can still see it here, but the pie chart kind of gives you the, um you know, it's all parts of 100%. So what I wrote down was the pie chart. It's more proportional information. You gonna tell the proportion out of 100% a little bit better for this data. All right, so that is our. That's what we need to do for this problem. Hope this helps. Shot makes sense. You stop. Let's a nice apple to use or doing it by hand would be a whole lot more difficult. You just kind of have to make sure be careful with scaling and, you know, label each of these titles there.

So we have. What we have done is we have made frequency distributions for both off the loot assets. So we're first data set is where the respondents live now, and the second data set is what would be their ideal community. So we have plotted all the data points according toe the frequency. So the frequencies, the number of times of value appears in their data sets. So city appears 32 times in this data set and another data set appears 24 times and so on. So then we will calculate the relative frequency creative frequency. It's nothing but frequency off a particular class divided by total number off data points in the data set. So, for example, for city for first data set the frequencies 32 32 divided by 100 will give us your A 1000.32 and the similar manner we will calculate the relative frequency for both their data sets all the data all the categories off, both their data sets. Then we will go ahead and applaud a bar graph on the to both the data sets on a similar bar graph. So in the horizontal axis, you can see that we have plotted the answers that we got from the respondents and on the whole particle axis, we have plotted the frequency eso once, er the c part of the question. We can see that most of the adults are living right now in city, so the answer will lease 60 or c on the deep part. We can see that we'll do most of the adults considered as the ideal community, so you can see that most of the adults would want toe move towards small towns or p mhm. And from the graph, we can conclude that less people will. We will. We will be living in cities and the most of the people will moved over the small towns and rural areas in future. And the number of people in the suburb do not change very much. You can see from to see from the bar graph. There is a lot of fluctuation here and here and here, but not that much at this part. Off the graph


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