Textbook in PDF format The high relevance of the topic of statistics and data analysis today is also illustrated by the extensive list of ongoing research projects involving many and di- verse industrial partners within these four sections. Neither society nor industry can cope with all the available data without using highly specialized people in statistical techniques, nor can they cope and be internationally competitive without continuously further developing these methodologies in research projects. Statistics is and will continue to be a relevant, viable and dynamic field. And the amount of experts in the field continues to be small compared to the demand for experts, hence obtaining skills in statistics is for sure a wise career choice for an engineer. Still for any engineer not specialising in statistics, a basic level of statistics understanding and data handling ability is crucial for the ability to navigate in modern society and business, which will be heavily influenced by data of many kinds in the future. This book is available in in two versions: one using the open souce environment R and one using the open source environment Python. You are currently reading the Python version, and this is the software used throughout the book for working with statistics, probability and data analysis. An introduction to Python is included in this chapter. Introduction, descriptive statistics, Python and data visualization Probability and simulation Statistical analysis of one and two sample data Statistics by simulation Simple linear regression Multiple linear regression Analysis of categorical data Analysis of variance (analysis of multi-group data)