1. Statistics

Despite popular opinion that statistics is not required for data science, there should be no surpise that this book has a strongly statistical flavor. By the end of this chapter I wish to move from ignorance of statistics to statistics of ignorance.

Statistics provides a set of systematic methods used to make inferences about a population based on . This chapter will cover critical topics such as:

1. Summary statistics
2. Confidence interval and p-value
3. Statistical models
4. Parameter estimation
5. Bias-variance tradeoff

This book primarily focuses on point estimation with little emphasis on interval estimation.