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Confidence interval for difference of mean
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According to my study, the confidence intervals for the difference in means provide a range of likely values for the difference between 2 population means. If 95% confidence interval for the difference of 2 sample means include null value, we can claim that there is no statically significant difference between the two groups.
For this comparison, do two populations need to be equivalent? Or can it be two different populations?
(Actual problem: I have test data collected from 2 test scenarios, where the settings of each test is different from each other. I want to compare the two mean values obtained from them. Note that the two distributions do not have normal shape (bell shape))
statistics confidence-interval
asked Aug 2 at 10:47
Pasindu
12
add a comment |Â
up vote
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down vote
favorite
According to my study, the confidence intervals for the difference in means provide a range of likely values for the difference between 2 population means. If 95% confidence interval for the difference of 2 sample means include null value, we can claim that there is no statically significant difference between the two groups.
For this comparison, do two populations need to be equivalent? Or can it be two different populations?
(Actual problem: I have test data collected from 2 test scenarios, where the settings of each test is different from each other. I want to compare the two mean values obtained from them. Note that the two distributions do not have normal shape (bell shape))
statistics confidence-interval
asked Aug 2 at 10:47
Pasindu
12
1
what you mean by saying "equivalent populations"?
– pointguard0
Aug 2 at 10:51
This is what I mean. Assume you do a sample test with several conditions. Then you do another sample test using another set of invariants. In that case two populations are not equivaluent right?
– Pasindu
Aug 2 at 11:05
add a comment |Â
up vote
0
down vote
favorite
up vote
0
down vote
favorite
According to my study, the confidence intervals for the difference in means provide a range of likely values for the difference between 2 population means. If 95% confidence interval for the difference of 2 sample means include null value, we can claim that there is no statically significant difference between the two groups.
For this comparison, do two populations need to be equivalent? Or can it be two different populations?
(Actual problem: I have test data collected from 2 test scenarios, where the settings of each test is different from each other. I want to compare the two mean values obtained from them. Note that the two distributions do not have normal shape (bell shape))
statistics confidence-interval
asked Aug 2 at 10:47
Pasindu
12
According to my study, the confidence intervals for the difference in means provide a range of likely values for the difference between 2 population means. If 95% confidence interval for the difference of 2 sample means include null value, we can claim that there is no statically significant difference between the two groups.
For this comparison, do two populations need to be equivalent? Or can it be two different populations?
(Actual problem: I have test data collected from 2 test scenarios, where the settings of each test is different from each other. I want to compare the two mean values obtained from them. Note that the two distributions do not have normal shape (bell shape))
statistics confidence-interval
asked Aug 2 at 10:47
Pasindu
12
edited Aug 2 at 11:03
asked Aug 2 at 10:47
Pasindu
12
asked Aug 2 at 10:47
Pasindu
12
asked Aug 2 at 10:47
Pasindu
12
12
1
what you mean by saying "equivalent populations"?
– pointguard0
Aug 2 at 10:51
This is what I mean. Assume you do a sample test with several conditions. Then you do another sample test using another set of invariants. In that case two populations are not equivaluent right?
– Pasindu
Aug 2 at 11:05
add a comment |Â
1
what you mean by saying "equivalent populations"?
– pointguard0
Aug 2 at 10:51
This is what I mean. Assume you do a sample test with several conditions. Then you do another sample test using another set of invariants. In that case two populations are not equivaluent right?
– Pasindu
Aug 2 at 11:05
1
1
what you mean by saying "equivalent populations"?
– pointguard0
Aug 2 at 10:51
what you mean by saying "equivalent populations"?
– pointguard0
Aug 2 at 10:51
This is what I mean. Assume you do a sample test with several conditions. Then you do another sample test using another set of invariants. In that case two populations are not equivaluent right?
– Pasindu
Aug 2 at 11:05
This is what I mean. Assume you do a sample test with several conditions. Then you do another sample test using another set of invariants. In that case two populations are not equivaluent right?
– Pasindu
Aug 2 at 11:05
add a comment |Â
1 Answer
1
active
oldest
votes
up vote
0
down vote
accepted
What you have described in your first paragraph assumes normality of datasets. So, if it is reasonable to make such assumption for the data collected in each of your scenarios then you can apply normal confidence interval method.
answered Aug 2 at 10:56
pointguard0
613517
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
add a comment |Â
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
What you have described in your first paragraph assumes normality of datasets. So, if it is reasonable to make such assumption for the data collected in each of your scenarios then you can apply normal confidence interval method.
answered Aug 2 at 10:56
pointguard0
613517
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
add a comment |Â
up vote
0
down vote
accepted
What you have described in your first paragraph assumes normality of datasets. So, if it is reasonable to make such assumption for the data collected in each of your scenarios then you can apply normal confidence interval method.
answered Aug 2 at 10:56
pointguard0
613517
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
add a comment |Â
up vote
0
down vote
accepted
up vote
0
down vote
accepted
What you have described in your first paragraph assumes normality of datasets. So, if it is reasonable to make such assumption for the data collected in each of your scenarios then you can apply normal confidence interval method.
answered Aug 2 at 10:56
pointguard0
613517
What you have described in your first paragraph assumes normality of datasets. So, if it is reasonable to make such assumption for the data collected in each of your scenarios then you can apply normal confidence interval method.
answered Aug 2 at 10:56
pointguard0
613517
answered Aug 2 at 10:56
pointguard0
613517
answered Aug 2 at 10:56
pointguard0
613517
answered Aug 2 at 10:56
pointguard0
613517
613517
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
add a comment |Â
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
No. In my datasets, original data doesn't have normal distribution. But according to central limit theorm, we can assume that mean values have a normal distribution, right?
– Pasindu
Aug 2 at 11:02
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
if the number of observations in each group is sufficiently large then yes.
– pointguard0
Aug 2 at 11:05
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
you can additionally plot the KDEs of each sample and compare the resulting plot with normal density.
– pointguard0
Aug 2 at 11:11
add a comment |Â
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1
what you mean by saying "equivalent populations"?
– pointguard0
Aug 2 at 10:51
This is what I mean. Assume you do a sample test with several conditions. Then you do another sample test using another set of invariants. In that case two populations are not equivaluent right?
– Pasindu
Aug 2 at 11:05