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The modeling example under the subtitle Value Conversions models the revenue generated for each visitor as: revenue = probability of paying at all * mean amount spent when paying.
The following priors are specified for the probability of purchase, theta, & mean purchase amount, lam, spent respectively:
Then, the following deterministic equation is used to calculate the average revenue per visitor, mu:
The calculation in the code:
Expected output
Shouldn't the calculation be mu = theta * lam, instead of mu = theta * (1 / lam)? Or am I missing something about the model specification?
The text was updated successfully, but these errors were encountered:
My mistake, it stems from the model specification indeed: lam in the model is the rate parameter for an Exponential distribution, so 1/lam is the mean.
Notebook title: Introduction to Bayesian A/B Testing
Notebook url: https://github.com/pymc-devs/pymc-examples/blob/main/examples/causal_inference/bayesian_ab_testing_introduction.ipynb
Issue description
The modeling example under the subtitle Value Conversions models the revenue generated for each visitor as:
revenue = probability of paying at all * mean amount spent when paying
.The following priors are specified for the probability of purchase,

theta
, & mean purchase amount,lam
, spent respectively:Then, the following deterministic equation is used to calculate the average revenue per visitor,

mu
:The calculation in the code:

Expected output
Shouldn't the calculation be
mu = theta * lam
, instead ofmu = theta * (1 / lam)
? Or am I missing something about the model specification?The text was updated successfully, but these errors were encountered: