Bereketoglu Abdullah Burkan
Even to this day, region and gender in many countries are believed to be one of the most important parameters to measure the pricing or cost of the health insurance that will apply to a person. Here in this study, the goal is to analyze causal inferences and effects of gender and region by Bayesian models built to measure the total and direct effect of gender and region. In the end, beliefs of region and gender are important parameters are discussed, and results from a conclusion are given on the case. The use of PyMC module embedded in the Python programming language is used as the main modeling method.
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