Preface

About the Writer

Bakti Siregar, M.Sc., CDSS works as a Lecturer at the ITSB Data Science Program. He earned his Master’s degree from the Department of Applied Mathematics at National Sun Yat Sen University, Taiwan. In addition to teaching, Bakti also works as a Freelance Data Scientist for leading companies such as JNE, Samora Group, Pertamina, and PT. Green City Traffic.

He has a strong enthusiasm for projects (and teaching) in the fields of Big Data Analytics, Machine Learning, Optimization, and Time Series Analysis, particularly in finance and investment. His core expertise lies in statistical programming languages such as R Studio and Python. He is also experienced in implementing database systems like MySQL/NoSQL for data management and is proficient in using Big Data tools such as Spark and Hadoop.

Some of his projects can be viewed here: Rpubs, Github, Website, and Kaggle


Acknowledgments

In an era dominated by data, mastering statistics is crucial for making evidence-based decisions and revealing meaningful patterns within complex datasets. This module introduces learners to the fundamental principles and methods of statistics, equipping them with the skills to explore, summarize, and interpret data effectively. This Book covers:

  • Introduction to statistics and its role in decision-making
  • Data types and collection methods for accurate and reliable analysis
  • Data presentation using clear tables, charts, and visual summaries
  • Measures of central tendency and dispersion to describe datasets
  • Probability concepts and probability distributions to quantify uncertainty
  • Confidence intervals and statistical inference for drawing robust conclusions
  • Nonparametric methods for analyzing data without strict distribution assumptions

By completing this module, learners will gain the analytical capabilities to manage real-world data, extract actionable insights, and communicate findings with clarity and rigor, establishing a strong foundation for advanced study or professional practice in data science, research, and industry.


Feedback & Suggestions

Your feedback is essential for improving the clarity, relevance, and usefulness of this module. Readers are invited to share their thoughts on the content, structure, and practical applications, as well as suggestions for new topics, examples, or tools.

This input helps make the E-book a more practical and comprehensive resource for Basic Statistics, bridging academic learning and real-world application. Thank you for contributing to the evolution of this material!

For feedback and suggestions, feel free to contact:

  • dsciencelabs@outlook.com
  • siregarbakti@gmail.com
  • siregarbakti@itsb.ac.id