Verify Account

This book is suitable for an introductory course of data analytics to help students understand some main statistical learning models, such as linear regression, logistic regression, tree models and random forests, ensemble learning, sparse learning, principal component analysis, kernel methods including the support vector machine and kernel regression, etc. Data science practice is a process that should be told as a story, rather than a one-time implementation of one single model. This process is a main focus of this book, with many course materials about exploratory data analysis, residual analysis, and flowcharts to develop and validate models and data pipelines.

An instructors will find graphical illustrations to explain some methods to students. On a larger scale, the connection between classic statistical models with machine learning algorithms is illustrated by focusing on the understanding of the iterative nature of the computational algorithms enabled by computers. We help students develop an eye for a method’s connection with other models that only appear to be different. This understanding will help us know a method’s strength and limitations, the importance of the context, and the assumptions we have carried in our data analysis.

An important for students to understand the storytelling component of data science. Data scientists tell stories every day. A story conveys a message, and a skilful data scientist must have the experience that the message changes its shape and meaning, depending on which model is used, how the model is tuned, or what part of the data is used. And some models have assumed a particular storytelling mode or structure. For example, we found hypothesis testing is a difficult concept for students to understand its essence, because it is a “negative” reading of data. It is not to translate what the data says, but to seek evidence from data against the null hypothesis we will need to come up with first. Examples as such will be found in the book to help students have a larger and deeper view of what they will learn.