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How does a frequency polygon differ from a histogram?

Both are graphs that illustrate a grouped frequency distribution.

A histogram is a bar graph,

with the width of each bar being determined by the length of intervals, and height by the frequency.

A frequency polygon is a line graph,

which uses the histogram by joining consecutive midpoints of the tops of the histogram bars with straight line segments.

The midpoints of the first and last bars are joined to endpoints on the horizontal axis where the adjoining midpoints would appear.

Multivariable Optimization

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this question asks you to talk about Thea. Difference is what sets a hist a gram apart from a frequency polygon. So get a history Graham and a frequency polygon. So we know what a history it looks like when we have a history. Graham and a couple of Bin's bins being ranges for the data to fall in will get bars like this A history. Graham is a type of bar graph, and I know I'm drawing them overlapping. That's not really what I meant to dio, but it looks like this. Imagine that these were straight lines. Um, history is a type of bar graph, and it shows the frequency of the amount of data that's within each range. So it will look something like this. Now, this is pretty similar to a frequency polygon. If we if we imagine that we had the same data that I just made up for the history Graham here. Ah, frequency polygon would look something like, uh, like this where it goes and touches each midpoint. Um, something like that. It's hard to see because this line is so straight here. Um, but it is a similar sort of display of what the distribution of data would be. Here, Um, we're grouping it into sections that we can clearly see. I clearly have differences. And here what you do in a frequency polygon is you connect the tops the mid points of each of the, uh, bars in the history. Graham. So you're still working with the ranges? Um, and you're still grouping the data together. But this time, instead of showing, um, the with of the range and the height of the, uh, the the frequency, you're only showing the height of the midpoint of the frequency. And it it leads CIA, the viewer to believe that there's a higher frequency of numbers between these two mid points than there are between these two mid points. Now, that might be true. That might not Here, um, in a hist a gram. All we know is that, um the range is the the amounts of data between the endpoints or the bins, the brakes and the bins. Um, we know that if this has been B and this has been a we know that there are more and been be than there are in a We don't really have that luxury with a frequency polygon because we could sort of assume that there are beings anywhere I could make this a been it contains. Ah, a little bit of the first, the third bar and a little bit of the fourth bar, and we don't really know exactly how much is in there. Um, so that's one of the drawbacks with a frequency, probably guns. You're not exactly sure about the bins, but it both still give you a general idea of the shape of the data and where it's centered and how far it's spread out.