Preface
About the Writer
Bakti Siregar, M.Sc., CDS is a Lecturer in the Data Science Program at ITSB. He obtained his Master’s degree in Applied Mathematics from the National Sun Yat-sen University, Taiwan. Alongside his academic role, Bakti also serves as a Freelance Data Scientist, collaborating with leading companies such as JNE, Samora Group, Pertamina, and PT. Green City Traffic.
His professional and research interests include Big Data Analytics, Machine Learning, Optimization, and Time Series Analysis, with a particular focus on finance and investment applications. His core expertise lies in statistical programming using R and Python, complemented by strong experience in database management systems such as MySQL and NoSQL. In addition, he is proficient in applying Big Data technologies, including Spark and Hadoop, for large-scale data processing and analysis.
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 Introduction to 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