Causal Inference in Python. Causal Relationships in IT Development

Causal Inference in Python. Causal Relationships in IT Development

How many customers will an additional dollar spent on online advertising attract? Which customers will only buy when given a discount coupon? How to determine the optimal pricing strategy? The best way to find out how the levers we have... at our disposal affect the business metrics we want to achieve is causal inference.
Mateusz Fakur, a senior data analysis specialist at Nibank, discusses the largely untapped potential of causal inference for assessing consequences and effects. Managers, data processing specialists, and business analysts will get acquainted with classical methods of visual inference, such as randomized controlled trials (A/B tests), linear regression, propensity score matching, synthetic controls, and difference in differences. Each method is accompanied by a real-life example.

Author: Матеуш Факур

Printhouse: piter

Series: O'Reilly Bestsellers

Year of publication: 2025

ISBN: 9786010843547

Number of pages: 400

Size: 234х165х23 mm

Cover type: soft

Weight: 400 g

ID: 1690848

How many customers will an additional dollar spent on online advertising attract? Which customers will only buy when given a discount coupon? How to determine the optimal pricing strategy? The best way to find out how the levers we have at our disposal affect the business metrics we want to achieve is causal inference.
Mateusz Fakur, a senior data analysis specialist at Nibank, discusses the largely untapped potential of causal inference for assessing consequences and effects. Managers, data processing specialists, and business analysts will get acquainted with classical methods of visual inference, such as randomized controlled trials (A/B tests), linear regression, propensity score matching, synthetic controls, and difference in differences. Each method is accompanied by a real-life example.

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