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I'm a confused. Are you saying that a chart isn't a histogram unless each bar represents the same number of items? I'm not sure I've even seen a chart like that

by Bjartr 3y ago

I'm a confused. Are you saying that a chart isn't a histogram unless each bar represents the same number of items? I'm not sure I've even seen a chart like that before, I'd love to see an example if you've got one handy.

kergonath 3y ago
The parent is more confused than you are, I think. I have almost never seen an histogram with bins of unequal sizes. The claims were dubious so I checked Wikipedia, which mentions this: > The bins (intervals) must be adjacent and are often (but not required to be) of equal size. And this: > A histogram is used for continuous data, where the bins represent ranges of data, while a bar chart is a plot of categorical variables. To be fair, there probably are variations in nomenclature across fields. But saying that a histogram with bins of equal width is a bar chart is wrong, at least in the general sense.
fsckboy 3y ago
It's what I was taught in statistics class at MIT. But you're right, I rarely see them, people just call bar charts "histograms". What it does is smooth out outliers. There is always (i mean, within reason) a good sample at the mean, but as you go out from the mean you get more and more variance (it's sort of the definition of variance) A gaussian bell curve is a "population density function" and this definition of histogram reflects keeping the population density meaningful in terms of height. I will try to look for some. But the wikipedia article on histograms does reference them, that's what they are talking about wrt "varying width" bar charts. It's just that there is a rule to varying the width, "x times y is equal for all the rectangles" (oh yeah, you even get to "eyeball it" to make them. Unless you have a massive number of sample points, if you can choose a width parameter that makes your curve look normal, your curve probably is normal, or at least, you can't say that it's not, no matter what the bar chart looks like. to put it another way, if you follow this rule for a perfect normal distribution, you'll still get a plot of a perfect normal distribution. But if you have a sparse sample that's a jaggy bell curve, it will move the curve toward a smoother curve, accurate in the sense of "this curve is statistically equivalent to your data, so if it looks "normal", probably your data is normal, and you won't imagine a mode where there isn't one.

by Bjartr 3y ago

kergonath 3y ago

The parent is more confused than you are, I think. I have almost never seen an histogram with bins of unequal sizes. The claims were dubious so I checked Wikipedia, which mentions this: > The bins (intervals) must be adjacent and are often (but not required to be) of equal size. And this: > A histogram is used for continuous data, where the bins represent ranges of data, while a bar chart is a plot of categorical variables. To be fair, there probably are variations in nomenclature across fields. But saying that a histogram with bins of equal width is a bar chart is wrong, at least in the general sense.

fsckboy 3y ago

It's what I was taught in statistics class at MIT. But you're right, I rarely see them, people just call bar charts "histograms". What it does is smooth out outliers. There is always (i mean, within reason) a good sample at the mean, but as you go out from the mean you get more and more variance (it's sort of the definition of variance) A gaussian bell curve is a "population density function" and this definition of histogram reflects keeping the population density meaningful in terms of height. I will try to look for some. But the wikipedia article on histograms does reference them, that's what they are talking about wrt "varying width" bar charts. It's just that there is a rule to varying the width, "x times y is equal for all the rectangles" (oh yeah, you even get to "eyeball it" to make them. Unless you have a massive number of sample points, if you can choose a width parameter that makes your curve look normal, your curve probably is normal, or at least, you can't say that it's not, no matter what the bar chart looks like. to put it another way, if you follow this rule for a perfect normal distribution, you'll still get a plot of a perfect normal distribution. But if you have a sparse sample that's a jaggy bell curve, it will move the curve toward a smoother curve, accurate in the sense of "this curve is statistically equivalent to your data, so if it looks "normal", probably your data is normal, and you won't imagine a mode where there isn't one.