Linear Regression Analysis and Modelling at MeasureCamp Amsterdam 2019
Linear regression analysis and modelling
#MeasureCampNL – April 13, 2019
Petri Mertanen https://www.linkedin.com/in/petrimertanen/
• BBA – Marketing, Specialist Qualification in Management
• (Digital) Analytics exprerience since 2005
• Lecturer of Aalto University 2017-2018
• Elements of Artificial Intelligence: https://www.elementsofai.com/
• Statistical thinking for Data Science and Analytics:
• Google Analytics Individual Qualification, Google Ads Fundamentals, Google Tag Manager
Fundamentals, Introduction to Data Studio
• Econometrics Course at Aalto University
• Marketing Analytics (slides by Aalto University)
• MeasureCamp Amsterdam 2017: Predictive Conversion Modelling
• MeasureCamp Amsterdam 2018: From Digital Attribution to Marketing Mix Modelling
About linear regression
• In statistics, linear regression is a linear approach to modelling the relationship between
a response (objective) and one or more explanatory variables.
• The case of one explanatory variable is called simple linear regression. For more than one
explanatory variable, the process is called multiple linear regression.
• Basically, we want to explain (mathematically) what things (variables or parameters)
cause the certain outputs.
• Linear regression is well known algorithm for supervised learning.
• This technique is widely applied across industries and is simple to understand, allowing
for high interpretability.
• Linear Regression is commonly used for analyzing biological systems, marketing and
product performance, market research studies, sales forecasting, and stock market
About the case and data preparation
• Major “healthcare” player in Finland.
• 46 % of bookings come from online.
• Mostly used paid search (Google Ads), Facebook
and display as digital advertising channels.
• Paid search being clearly the biggest channel
according to money spent.
• Data collected during Q1/2019 on daily level.
• You can do the data cleaning manually in Excel.
• Or you can automate the data collection, for
example with Supermetrics (from Finland!).