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📚 Principles of Data Science
Chapters ▾
1 What Are Data and Data Science?2 Collecting and Preparing Data3 Descriptive Statistics: Statistical Measurements and Probability Distributions4 Inferential Statistics and Regression Analysis5 Time Series and Forecasting6 Decision-Making Using Machine Learning Basics7 Deep Learning and AI Basics8 Ethics Throughout the Data Science Cycle9 Visualizing Data10 Reporting Results

Chapter 10: Reporting Results

Five people with laptops at a conference table.
Figure 10.1 The report is key: When done well, data science reports provide evidence-based insights that promote transparency by documenting methods and assumptions used, help identify risks and opportunities, and support decision-making.The report is key: When done well, data science reports provide evidence-based insights that promote transparency by documenting methods and assumptions used, help identify risks and opportunities, and support decision-making. (credit: "CC-BY-Mapbox-Uncharted-ERG_Mapbox-b041” by Mapbox/Flickr, CC BY 2.0)

Data science is not just about analyzing datasets. Communicating the findings effectively is an essential part of the process aimed at promoting understanding and retention of key information. The ability to convey complex information to various kinds of audiences in a clear, consumable, and accessible manner is a vital skill for any data scientist. This chapter is designed to equip you with the skills necessary to create informative reports that combine analytical rigor and clarity. You will learn how to identify and engage your audience, document the intricate methods that underpin your data science projects, and determine the most compelling ways to present your data, analysis, and findings.