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Is it 40% or 0.4%?
$begingroup$
A variable, which should contain percents, also contains some "ratio" values, for example:
0.61
41
54
.4
.39
20
52
0.7
12
70
82
The real distribution parameters are unknown but I guess it is unimodal with most (say over 70% of) values occurring between 50% and 80%, but it is also possible to see very low values (e.g., 0.1%).
Is there any formal or systematic approaches to determine the likely format in which each value is recorded (i.e., ratio or percent), assuming no other variables are available?
data-cleaning
asked 4 hours ago
OrionOrion
5311
$endgroup$
|
show 1 more comment
$begingroup$
A variable, which should contain percents, also contains some "ratio" values, for example:
0.61
41
54
.4
.39
20
52
0.7
12
70
82
The real distribution parameters are unknown but I guess it is unimodal with most (say over 70% of) values occurring between 50% and 80%, but it is also possible to see very low values (e.g., 0.1%).
Is there any formal or systematic approaches to determine the likely format in which each value is recorded (i.e., ratio or percent), assuming no other variables are available?
data-cleaning
asked 4 hours ago
OrionOrion
5311
$endgroup$
1
$begingroup$
I'm voting to close this question as off-topic because it is impossible to definitively answer. If you don't know what the data mean, how will strangers on the internet know?
$endgroup$
– Sycorax
4 hours ago
$begingroup$
Read it again. It is not about asking strangers on the Internet to guess the data mean.
$endgroup$
– Orion
4 hours ago
2
$begingroup$
What the data mean != what is the (data) mean.
$endgroup$
– Nick Cox
3 hours ago
$begingroup$
Oh, Ok. Correction: The question is not about asking strangers on the Internet what the data mean. Hooray.
$endgroup$
– Orion
3 hours ago
1
$begingroup$
You have 3 options: your big numbers are falsely big, and need a decimal in front; your small numbers are falsely small and need 100x multiplie; or your data is just fine. Why don't you plot the qqnorm of all three options?
$endgroup$
– EngrStudent
3 hours ago
|
show 1 more comment
$begingroup$
A variable, which should contain percents, also contains some "ratio" values, for example:
0.61
41
54
.4
.39
20
52
0.7
12
70
82
The real distribution parameters are unknown but I guess it is unimodal with most (say over 70% of) values occurring between 50% and 80%, but it is also possible to see very low values (e.g., 0.1%).
Is there any formal or systematic approaches to determine the likely format in which each value is recorded (i.e., ratio or percent), assuming no other variables are available?
data-cleaning
asked 4 hours ago
OrionOrion
5311
$endgroup$
A variable, which should contain percents, also contains some "ratio" values, for example:
0.61
41
54
.4
.39
20
52
0.7
12
70
82
The real distribution parameters are unknown but I guess it is unimodal with most (say over 70% of) values occurring between 50% and 80%, but it is also possible to see very low values (e.g., 0.1%).
Is there any formal or systematic approaches to determine the likely format in which each value is recorded (i.e., ratio or percent), assuming no other variables are available?
data-cleaning
data-cleaning
asked 4 hours ago
OrionOrion
5311
asked 4 hours ago
OrionOrion
5311
edited 3 hours ago
Orion
asked 4 hours ago
OrionOrion
5311
asked 4 hours ago
OrionOrion
5311
asked 4 hours ago
OrionOrion
5311
5311
1
$begingroup$
I'm voting to close this question as off-topic because it is impossible to definitively answer. If you don't know what the data mean, how will strangers on the internet know?
$endgroup$
– Sycorax
4 hours ago
$begingroup$
Read it again. It is not about asking strangers on the Internet to guess the data mean.
$endgroup$
– Orion
4 hours ago
2
$begingroup$
What the data mean != what is the (data) mean.
$endgroup$
– Nick Cox
3 hours ago
$begingroup$
Oh, Ok. Correction: The question is not about asking strangers on the Internet what the data mean. Hooray.
$endgroup$
– Orion
3 hours ago
1
$begingroup$
You have 3 options: your big numbers are falsely big, and need a decimal in front; your small numbers are falsely small and need 100x multiplie; or your data is just fine. Why don't you plot the qqnorm of all three options?
$endgroup$
– EngrStudent
3 hours ago
|
show 1 more comment
1
$begingroup$
I'm voting to close this question as off-topic because it is impossible to definitively answer. If you don't know what the data mean, how will strangers on the internet know?
$endgroup$
– Sycorax
4 hours ago
$begingroup$
Read it again. It is not about asking strangers on the Internet to guess the data mean.
$endgroup$
– Orion
4 hours ago
2
$begingroup$
What the data mean != what is the (data) mean.
$endgroup$
– Nick Cox
3 hours ago
$begingroup$
Oh, Ok. Correction: The question is not about asking strangers on the Internet what the data mean. Hooray.
$endgroup$
– Orion
3 hours ago
1
$begingroup$
You have 3 options: your big numbers are falsely big, and need a decimal in front; your small numbers are falsely small and need 100x multiplie; or your data is just fine. Why don't you plot the qqnorm of all three options?
$endgroup$
– EngrStudent
3 hours ago
1
1
$begingroup$
I'm voting to close this question as off-topic because it is impossible to definitively answer. If you don't know what the data mean, how will strangers on the internet know?
$endgroup$
– Sycorax
4 hours ago
$begingroup$
I'm voting to close this question as off-topic because it is impossible to definitively answer. If you don't know what the data mean, how will strangers on the internet know?
$endgroup$
– Sycorax
4 hours ago
$begingroup$
Read it again. It is not about asking strangers on the Internet to guess the data mean.
$endgroup$
– Orion
4 hours ago
$begingroup$
Read it again. It is not about asking strangers on the Internet to guess the data mean.
$endgroup$
– Orion
4 hours ago
2
2
$begingroup$
What the data mean != what is the (data) mean.
$endgroup$
– Nick Cox
3 hours ago
$begingroup$
What the data mean != what is the (data) mean.
$endgroup$
– Nick Cox
3 hours ago
$begingroup$
Oh, Ok. Correction: The question is not about asking strangers on the Internet what the data mean. Hooray.
$endgroup$
– Orion
3 hours ago
$begingroup$
Oh, Ok. Correction: The question is not about asking strangers on the Internet what the data mean. Hooray.
$endgroup$
– Orion
3 hours ago
1
1
$begingroup$
You have 3 options: your big numbers are falsely big, and need a decimal in front; your small numbers are falsely small and need 100x multiplie; or your data is just fine. Why don't you plot the qqnorm of all three options?
$endgroup$
– EngrStudent
3 hours ago
$begingroup$
You have 3 options: your big numbers are falsely big, and need a decimal in front; your small numbers are falsely small and need 100x multiplie; or your data is just fine. Why don't you plot the qqnorm of all three options?
$endgroup$
– EngrStudent
3 hours ago
|
show 1 more comment
2 Answers
2
active
oldest
votes
$begingroup$
Assuming
- The only data you have is the percents/ratios (no other related explanatory variables)
- Your percents comes from a unimodel distribution $P$ and the ratios come from the same unimodal distribution $P$, but squished by $100$ (call it $P_{100}$).
- The percent/ratios are all between $0$ and $100$.
Then there's a single cutoff point $K$ (with $K < 1.0$ obviously) where everything under $K$ is more likely to be sampled from $P_{100}$ and everything over $K$ is more likely to be sampled from $P$.
You should be able to set up a maximum likelihood function with a binary parameter on each datapoint, plus any parameters of your chosen P.
Afterwards, find $K :=$ where $P$ and $P_{100}$ intersect and you can use that to clean your data.
In practice, just split your data 0-1 and 1-100, fit and plot both histograms and fiddle around with what you think $K$ is.
answered 2 hours ago
djmadjma
63947
$endgroup$
add a comment |
$begingroup$
Here's one method of determining whether your data are percents or proportions: if there are out-of-bounds values for a proportion (e.g. 52, 70, 82, 41, 54, to name a few) then they must be percents.
Therefore, your data must be percents. You're welcome.
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
$endgroup$
3
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
1
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
add a comment |
Your Answer
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
Assuming
- The only data you have is the percents/ratios (no other related explanatory variables)
- Your percents comes from a unimodel distribution $P$ and the ratios come from the same unimodal distribution $P$, but squished by $100$ (call it $P_{100}$).
- The percent/ratios are all between $0$ and $100$.
Then there's a single cutoff point $K$ (with $K < 1.0$ obviously) where everything under $K$ is more likely to be sampled from $P_{100}$ and everything over $K$ is more likely to be sampled from $P$.
You should be able to set up a maximum likelihood function with a binary parameter on each datapoint, plus any parameters of your chosen P.
Afterwards, find $K :=$ where $P$ and $P_{100}$ intersect and you can use that to clean your data.
In practice, just split your data 0-1 and 1-100, fit and plot both histograms and fiddle around with what you think $K$ is.
answered 2 hours ago
djmadjma
63947
$endgroup$
add a comment |
$begingroup$
Assuming
- The only data you have is the percents/ratios (no other related explanatory variables)
- Your percents comes from a unimodel distribution $P$ and the ratios come from the same unimodal distribution $P$, but squished by $100$ (call it $P_{100}$).
- The percent/ratios are all between $0$ and $100$.
Then there's a single cutoff point $K$ (with $K < 1.0$ obviously) where everything under $K$ is more likely to be sampled from $P_{100}$ and everything over $K$ is more likely to be sampled from $P$.
You should be able to set up a maximum likelihood function with a binary parameter on each datapoint, plus any parameters of your chosen P.
Afterwards, find $K :=$ where $P$ and $P_{100}$ intersect and you can use that to clean your data.
In practice, just split your data 0-1 and 1-100, fit and plot both histograms and fiddle around with what you think $K$ is.
answered 2 hours ago
djmadjma
63947
$endgroup$
add a comment |
$begingroup$
Assuming
- The only data you have is the percents/ratios (no other related explanatory variables)
- Your percents comes from a unimodel distribution $P$ and the ratios come from the same unimodal distribution $P$, but squished by $100$ (call it $P_{100}$).
- The percent/ratios are all between $0$ and $100$.
Then there's a single cutoff point $K$ (with $K < 1.0$ obviously) where everything under $K$ is more likely to be sampled from $P_{100}$ and everything over $K$ is more likely to be sampled from $P$.
You should be able to set up a maximum likelihood function with a binary parameter on each datapoint, plus any parameters of your chosen P.
Afterwards, find $K :=$ where $P$ and $P_{100}$ intersect and you can use that to clean your data.
In practice, just split your data 0-1 and 1-100, fit and plot both histograms and fiddle around with what you think $K$ is.
answered 2 hours ago
djmadjma
63947
$endgroup$
Assuming
- The only data you have is the percents/ratios (no other related explanatory variables)
- Your percents comes from a unimodel distribution $P$ and the ratios come from the same unimodal distribution $P$, but squished by $100$ (call it $P_{100}$).
- The percent/ratios are all between $0$ and $100$.
Then there's a single cutoff point $K$ (with $K < 1.0$ obviously) where everything under $K$ is more likely to be sampled from $P_{100}$ and everything over $K$ is more likely to be sampled from $P$.
You should be able to set up a maximum likelihood function with a binary parameter on each datapoint, plus any parameters of your chosen P.
Afterwards, find $K :=$ where $P$ and $P_{100}$ intersect and you can use that to clean your data.
In practice, just split your data 0-1 and 1-100, fit and plot both histograms and fiddle around with what you think $K$ is.
answered 2 hours ago
djmadjma
63947
answered 2 hours ago
djmadjma
63947
answered 2 hours ago
djmadjma
63947
answered 2 hours ago
djmadjma
63947
63947
add a comment |
add a comment |
$begingroup$
Here's one method of determining whether your data are percents or proportions: if there are out-of-bounds values for a proportion (e.g. 52, 70, 82, 41, 54, to name a few) then they must be percents.
Therefore, your data must be percents. You're welcome.
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
$endgroup$
3
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
1
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
add a comment |
$begingroup$
Here's one method of determining whether your data are percents or proportions: if there are out-of-bounds values for a proportion (e.g. 52, 70, 82, 41, 54, to name a few) then they must be percents.
Therefore, your data must be percents. You're welcome.
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
$endgroup$
3
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
1
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
add a comment |
$begingroup$
Here's one method of determining whether your data are percents or proportions: if there are out-of-bounds values for a proportion (e.g. 52, 70, 82, 41, 54, to name a few) then they must be percents.
Therefore, your data must be percents. You're welcome.
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
$endgroup$
Here's one method of determining whether your data are percents or proportions: if there are out-of-bounds values for a proportion (e.g. 52, 70, 82, 41, 54, to name a few) then they must be percents.
Therefore, your data must be percents. You're welcome.
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
answered 3 hours ago
beta1_equals_beta2beta1_equals_beta2
412
412
3
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
1
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
add a comment |
3
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
1
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
3
3
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
$begingroup$
The issue is that the two are mixed together. It’s not all percents or all ratios/proportions. 49 is a percentage, but 0.49 could be either.
$endgroup$
– The Laconic
3 hours ago
1
1
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
$begingroup$
If you can't assume there is a unified format for all of the rows, then the question is obviously unanswerable. In the absence of any other information, it's anyone's guess whether the 0.4 is a proportion of a percentage. I chose to answer the only possible answerable interpretation of the question.
$endgroup$
– beta1_equals_beta2
3 hours ago
add a comment |
Thanks for contributing an answer to Cross Validated!
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But avoid …
- Asking for help, clarification, or responding to other answers.
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1
$begingroup$
I'm voting to close this question as off-topic because it is impossible to definitively answer. If you don't know what the data mean, how will strangers on the internet know?
$endgroup$
– Sycorax
4 hours ago
$begingroup$
Read it again. It is not about asking strangers on the Internet to guess the data mean.
$endgroup$
– Orion
4 hours ago
2
$begingroup$
What the data mean != what is the (data) mean.
$endgroup$
– Nick Cox
3 hours ago
$begingroup$
Oh, Ok. Correction: The question is not about asking strangers on the Internet what the data mean. Hooray.
$endgroup$
– Orion
3 hours ago
1
$begingroup$
You have 3 options: your big numbers are falsely big, and need a decimal in front; your small numbers are falsely small and need 100x multiplie; or your data is just fine. Why don't you plot the qqnorm of all three options?
$endgroup$
– EngrStudent
3 hours ago