Book contents
- A Hands-On Introduction to Data Science
- A Hands-On Introduction to Data Science
- Copyright page
- Contents
- Preface
- About the Author
- Part I Conceptual Introductions
- 1 Introduction
- 2 Data
- 3 Techniques
- Part II Tools for Data Science
- Part III Machine Learning for Data Science
- Part IV Applications, Evaluations, and Methods
- Book part
- Index
- References
3 - Techniques
from Part I - Conceptual Introductions
Published online by Cambridge University Press: aN Invalid Date NaN
Book contents
- A Hands-On Introduction to Data Science
- A Hands-On Introduction to Data Science
- Copyright page
- Contents
- Preface
- About the Author
- Part I Conceptual Introductions
- 1 Introduction
- 2 Data
- 3 Techniques
- Part II Tools for Data Science
- Part III Machine Learning for Data Science
- Part IV Applications, Evaluations, and Methods
- Book part
- Index
- References
Summary
This chapter explores fundamental analytical techniques in data science, distinguishing between data analysis (backward-looking) and data analytics (forward-looking prediction).
Six key analysis categories are covered:
Descriptive Analysis examines current data through statistical measures (mean, median, mode) and visualizations to understand "what is happening."
Diagnostic Analytics investigates "why something happened" using correlation analysis, emphasizing the distinction between correlation and causation.
Predictive Analytics forecasts future outcomes using historical data and regression analysis.
Prescriptive Analytics determines optimal courses of action by analyzing potential decisions.
Exploratory Analysis discovers unknown relationships through visualization when questions aren’t predetermined.
Mechanistic Analysis examines exact variable changes and their effects.
The chapter emphasizes statistical literacy as essential for data scientists, covering key concepts like variable types, frequency distributions, measures of centrality and dispersion, and regression modeling. Hands-on examples demonstrate applications across business, healthcare, and social sciences.
Keywords
Information
- Type
- Chapter
- Information
- A Hands-On Introduction to Data Science with Python , pp. 75 - 108Publisher: Cambridge University PressPrint publication year: 2026
References
Further Reading and Resources
• Krathwohl, D. R. (2009). Methods of Educational and Social Science Research: The Logic of Methods. Waveland Press.Google Scholar
• A video by IBM describes the progression from descriptive analytics, through predictive analytics, to prescriptive analytics: https://www.youtube.com/watch?v=VtETirgVn9cGoogle Scholar
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