Mixing
bootstrap A/B testing
I have a question about bootstrapping testing. Recently, I designed an experiment with ~400K users on test and control group separately. one of the metric I tried to test was the mean of pave views difference on a specific page. When I used traditional t-test, I got a normal confidence interval with p-value less than 0.0001. Then I tried to use the bootstrap method covered in the class. What I did was take ~10,000 sample size and did 100,000 times replaced tests to calculate the mean differences between test and control group. Then the p-vale I got was as large as 0.9. I checked my code and everything looks good. Does anyone have some ideas about this discrepancy?
Here's the result from t-test
enter image description here
Here's the distribution of the mean_diff assume null is correct:
enter image description here
python ab-testing
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
add a comment |
I have a question about bootstrapping testing. Recently, I designed an experiment with ~400K users on test and control group separately. one of the metric I tried to test was the mean of pave views difference on a specific page. When I used traditional t-test, I got a normal confidence interval with p-value less than 0.0001. Then I tried to use the bootstrap method covered in the class. What I did was take ~10,000 sample size and did 100,000 times replaced tests to calculate the mean differences between test and control group. Then the p-vale I got was as large as 0.9. I checked my code and everything looks good. Does anyone have some ideas about this discrepancy?
Here's the result from t-test
enter image description here
Here's the distribution of the mean_diff assume null is correct:
enter image description here
python ab-testing
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
Please add your code to the question.
– Filnor
Nov 20 '18 at 6:52
add a comment |
I have a question about bootstrapping testing. Recently, I designed an experiment with ~400K users on test and control group separately. one of the metric I tried to test was the mean of pave views difference on a specific page. When I used traditional t-test, I got a normal confidence interval with p-value less than 0.0001. Then I tried to use the bootstrap method covered in the class. What I did was take ~10,000 sample size and did 100,000 times replaced tests to calculate the mean differences between test and control group. Then the p-vale I got was as large as 0.9. I checked my code and everything looks good. Does anyone have some ideas about this discrepancy?
Here's the result from t-test
enter image description here
Here's the distribution of the mean_diff assume null is correct:
enter image description here
python ab-testing
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
I have a question about bootstrapping testing. Recently, I designed an experiment with ~400K users on test and control group separately. one of the metric I tried to test was the mean of pave views difference on a specific page. When I used traditional t-test, I got a normal confidence interval with p-value less than 0.0001. Then I tried to use the bootstrap method covered in the class. What I did was take ~10,000 sample size and did 100,000 times replaced tests to calculate the mean differences between test and control group. Then the p-vale I got was as large as 0.9. I checked my code and everything looks good. Does anyone have some ideas about this discrepancy?
Here's the result from t-test
enter image description here
Here's the distribution of the mean_diff assume null is correct:
enter image description here
python ab-testing
python ab-testing
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
asked Nov 20 '18 at 6:48
Bangyu MaoBangyu Mao
1
1
Please add your code to the question.
– Filnor
Nov 20 '18 at 6:52
add a comment |
Please add your code to the question.
– Filnor
Nov 20 '18 at 6:52
Please add your code to the question.
– Filnor
Nov 20 '18 at 6:52
Please add your code to the question.
– Filnor
Nov 20 '18 at 6:52
add a comment |
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Please add your code to the question.
– Filnor
Nov 20 '18 at 6:52