Finding P value - Explain
$begingroup$
def get_pvalue(con_conv, test_conv,con_size, test_size,):
lift = - abs(test_conv - con_conv)
scale_one = con_conv * (1 - con_conv) * (1 / con_size)
scale_two = test_conv * (1 - test_conv) * (1 / test_size)
scale_val = (scale_one + scale_two)**0.5
p_value = 2 * stats.norm.cdf(lift, loc = 0, scale = scale_val )
return p_value
I have this function and I would like to know that what it is actually doing and how it is actually calculating the p-value.
This is to find the difference between the conversion rate of control and test and group from an A/B test.
con_conv--> Conversion rate for control group
test_conv--> Conversion rate for test group
con_size --> population size for control group
test_size --> population size for test group
I understand that at scale_one and scale_two they are calculating the variance for each group but I don't understand that why they are adding both of them to calculate the standard deviation and why they are multiplying the cdf with 2 to get the p_value. If anyone can explain that would be awesome!
python statistics
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
def get_pvalue(con_conv, test_conv,con_size, test_size,):
lift = - abs(test_conv - con_conv)
scale_one = con_conv * (1 - con_conv) * (1 / con_size)
scale_two = test_conv * (1 - test_conv) * (1 / test_size)
scale_val = (scale_one + scale_two)**0.5
p_value = 2 * stats.norm.cdf(lift, loc = 0, scale = scale_val )
return p_value
I have this function and I would like to know that what it is actually doing and how it is actually calculating the p-value.
This is to find the difference between the conversion rate of control and test and group from an A/B test.
con_conv--> Conversion rate for control group
test_conv--> Conversion rate for test group
con_size --> population size for control group
test_size --> population size for test group
I understand that at scale_one and scale_two they are calculating the variance for each group but I don't understand that why they are adding both of them to calculate the standard deviation and why they are multiplying the cdf with 2 to get the p_value. If anyone can explain that would be awesome!
python statistics
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
def get_pvalue(con_conv, test_conv,con_size, test_size,):
lift = - abs(test_conv - con_conv)
scale_one = con_conv * (1 - con_conv) * (1 / con_size)
scale_two = test_conv * (1 - test_conv) * (1 / test_size)
scale_val = (scale_one + scale_two)**0.5
p_value = 2 * stats.norm.cdf(lift, loc = 0, scale = scale_val )
return p_value
I have this function and I would like to know that what it is actually doing and how it is actually calculating the p-value.
This is to find the difference between the conversion rate of control and test and group from an A/B test.
con_conv--> Conversion rate for control group
test_conv--> Conversion rate for test group
con_size --> population size for control group
test_size --> population size for test group
I understand that at scale_one and scale_two they are calculating the variance for each group but I don't understand that why they are adding both of them to calculate the standard deviation and why they are multiplying the cdf with 2 to get the p_value. If anyone can explain that would be awesome!
python statistics
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
def get_pvalue(con_conv, test_conv,con_size, test_size,):
lift = - abs(test_conv - con_conv)
scale_one = con_conv * (1 - con_conv) * (1 / con_size)
scale_two = test_conv * (1 - test_conv) * (1 / test_size)
scale_val = (scale_one + scale_two)**0.5
p_value = 2 * stats.norm.cdf(lift, loc = 0, scale = scale_val )
return p_value
I have this function and I would like to know that what it is actually doing and how it is actually calculating the p-value.
This is to find the difference between the conversion rate of control and test and group from an A/B test.
con_conv--> Conversion rate for control group
test_conv--> Conversion rate for test group
con_size --> population size for control group
test_size --> population size for test group
I understand that at scale_one and scale_two they are calculating the variance for each group but I don't understand that why they are adding both of them to calculate the standard deviation and why they are multiplying the cdf with 2 to get the p_value. If anyone can explain that would be awesome!
python statistics
python statistics
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
asked 1 min ago
Kartikeya SharmaKartikeya Sharma
101
101
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Kartikeya Sharma is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
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