Mixing
How to Group an Uneven Amount of Data into Classes in a Frequency Table
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I am currently in a "Statistics and Probability" course in college. We were taught to calculate the number of classes with the formula 3.33*log(N)+1. In my example, there were 40 data items, so the number of classes would be 6.33 = 6. The Cj (number of whole numbers in each row) is range / #classes. In my example, 48/6=8.
To construct the frequency table, we start with the first element (19 in this example), and add Cj-1 (7) to get the upper limit. So, 19-26, 27-34, etc. The data I am working with is only whole numbers.
My maximum is 67. If I construct the classes of the frequency table, it would look like this:
19-26
27-34
35-42
43-50
51-58
59-66
Unfortunately, this doesn't include 67. Should I simply add 1 to the last class (59-67), or would it be equally acceptable to add one to the upper limit of the first class, causing the intervals of each class to look like the following:
19-27
28-35
36-43
44-51
52-59
60-67
Which is the preffered method, or are both equally acceptable? Or is there another way?
Thank you for any and all help.
statistics
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
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add a comment |
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I am currently in a "Statistics and Probability" course in college. We were taught to calculate the number of classes with the formula 3.33*log(N)+1. In my example, there were 40 data items, so the number of classes would be 6.33 = 6. The Cj (number of whole numbers in each row) is range / #classes. In my example, 48/6=8.
To construct the frequency table, we start with the first element (19 in this example), and add Cj-1 (7) to get the upper limit. So, 19-26, 27-34, etc. The data I am working with is only whole numbers.
My maximum is 67. If I construct the classes of the frequency table, it would look like this:
19-26
27-34
35-42
43-50
51-58
59-66
Unfortunately, this doesn't include 67. Should I simply add 1 to the last class (59-67), or would it be equally acceptable to add one to the upper limit of the first class, causing the intervals of each class to look like the following:
19-27
28-35
36-43
44-51
52-59
60-67
Which is the preffered method, or are both equally acceptable? Or is there another way?
Thank you for any and all help.
statistics
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
$endgroup$
add a comment |
$begingroup$
I am currently in a "Statistics and Probability" course in college. We were taught to calculate the number of classes with the formula 3.33*log(N)+1. In my example, there were 40 data items, so the number of classes would be 6.33 = 6. The Cj (number of whole numbers in each row) is range / #classes. In my example, 48/6=8.
To construct the frequency table, we start with the first element (19 in this example), and add Cj-1 (7) to get the upper limit. So, 19-26, 27-34, etc. The data I am working with is only whole numbers.
My maximum is 67. If I construct the classes of the frequency table, it would look like this:
19-26
27-34
35-42
43-50
51-58
59-66
Unfortunately, this doesn't include 67. Should I simply add 1 to the last class (59-67), or would it be equally acceptable to add one to the upper limit of the first class, causing the intervals of each class to look like the following:
19-27
28-35
36-43
44-51
52-59
60-67
Which is the preffered method, or are both equally acceptable? Or is there another way?
Thank you for any and all help.
statistics
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
$endgroup$
I am currently in a "Statistics and Probability" course in college. We were taught to calculate the number of classes with the formula 3.33*log(N)+1. In my example, there were 40 data items, so the number of classes would be 6.33 = 6. The Cj (number of whole numbers in each row) is range / #classes. In my example, 48/6=8.
To construct the frequency table, we start with the first element (19 in this example), and add Cj-1 (7) to get the upper limit. So, 19-26, 27-34, etc. The data I am working with is only whole numbers.
My maximum is 67. If I construct the classes of the frequency table, it would look like this:
19-26
27-34
35-42
43-50
51-58
59-66
Unfortunately, this doesn't include 67. Should I simply add 1 to the last class (59-67), or would it be equally acceptable to add one to the upper limit of the first class, causing the intervals of each class to look like the following:
19-27
28-35
36-43
44-51
52-59
60-67
Which is the preffered method, or are both equally acceptable? Or is there another way?
Thank you for any and all help.
statistics
statistics
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
asked Jan 30 at 13:45
chessplayerjameschessplayerjames
1
1
add a comment |
add a comment |
1 Answer
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The preferred way to construct histogram boundaries is not trivial. Ideally, there are several things to consider:
- The bins should be of equal width.
- Choose the number of bins so that you can get a good picture of your data.
- No data point should fall on a boundary (in your case, with whole number data, you can just consider the boundaries to be on the halves so that this isn't an issue).
So you definitely don't want to make only one bin wider. I would recommend making all the bins wider by 1. It's far more preferable to have the lower end of the first bin be smaller than your minimum data point, than to have unequal width bins. The same goes for the high end: it's ok if the right-hand end of the highest bin is larger than the maximum of your data set.
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
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1 Answer
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1 Answer
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$begingroup$
The preferred way to construct histogram boundaries is not trivial. Ideally, there are several things to consider:
- The bins should be of equal width.
- Choose the number of bins so that you can get a good picture of your data.
- No data point should fall on a boundary (in your case, with whole number data, you can just consider the boundaries to be on the halves so that this isn't an issue).
So you definitely don't want to make only one bin wider. I would recommend making all the bins wider by 1. It's far more preferable to have the lower end of the first bin be smaller than your minimum data point, than to have unequal width bins. The same goes for the high end: it's ok if the right-hand end of the highest bin is larger than the maximum of your data set.
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
$endgroup$
add a comment |
$begingroup$
The preferred way to construct histogram boundaries is not trivial. Ideally, there are several things to consider:
- The bins should be of equal width.
- Choose the number of bins so that you can get a good picture of your data.
- No data point should fall on a boundary (in your case, with whole number data, you can just consider the boundaries to be on the halves so that this isn't an issue).
So you definitely don't want to make only one bin wider. I would recommend making all the bins wider by 1. It's far more preferable to have the lower end of the first bin be smaller than your minimum data point, than to have unequal width bins. The same goes for the high end: it's ok if the right-hand end of the highest bin is larger than the maximum of your data set.
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
$endgroup$
add a comment |
$begingroup$
The preferred way to construct histogram boundaries is not trivial. Ideally, there are several things to consider:
- The bins should be of equal width.
- Choose the number of bins so that you can get a good picture of your data.
- No data point should fall on a boundary (in your case, with whole number data, you can just consider the boundaries to be on the halves so that this isn't an issue).
So you definitely don't want to make only one bin wider. I would recommend making all the bins wider by 1. It's far more preferable to have the lower end of the first bin be smaller than your minimum data point, than to have unequal width bins. The same goes for the high end: it's ok if the right-hand end of the highest bin is larger than the maximum of your data set.
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
$endgroup$
The preferred way to construct histogram boundaries is not trivial. Ideally, there are several things to consider:
- The bins should be of equal width.
- Choose the number of bins so that you can get a good picture of your data.
- No data point should fall on a boundary (in your case, with whole number data, you can just consider the boundaries to be on the halves so that this isn't an issue).
So you definitely don't want to make only one bin wider. I would recommend making all the bins wider by 1. It's far more preferable to have the lower end of the first bin be smaller than your minimum data point, than to have unequal width bins. The same goes for the high end: it's ok if the right-hand end of the highest bin is larger than the maximum of your data set.
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
answered Jan 30 at 14:20
Adrian KeisterAdrian Keister
5,26971933
5,26971933
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