This online book is intended for beginners, college students and professionals confronted with statistical analyses. It is also a refresher for professional statisticians. The book covers over 600 concepts, chosen out of more than 1,500 for their popularity. Entries are listed in alphabetical order, and broken down into 18 parts. In addition to numerous illustrations, we have added 100 topics not covered in our online series Statistical Concepts Explained in Simple English. We also included a number of visualizations from our series Statistical Concepts Explained in One Picture, including:
- Bayes Theorem
- Naïve Bayes
- Confidence Intervals
- Three Types of Regression
- Support Vector Machines
- Hypothesis Tests
- Cross-validation
- Assumptions of Linear Regression
- R-squared
- Ensemble Methods
- Logistic Regression
- A/B Testing
- ROC Curve
- Sample Size Determination
- Determining the Number of Clusters
- EM Algorithm
- Azure Data Studio
- K Nearest Neighbors
- Prediction Algorithms
- Model Evaluation Techniques
The most recent version of this book is available from this link, accessible to DSC members only.
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About the author
Stephanie Glen is the founder of StatisticsHowTo.com, one of the most popular websites related to statistical education for non-statisticians, and also Editor at Data Science Central. Much of the material in this book points to articles on her website.
Other DSC books
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Credit: Data Science Central By: Vincent Granville
