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Description
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Making Sense of Data covers a series of technical topics that address how to analyze data. The book is divided into five parts: Introduction; Tables, Graphs, and Statistics; Grouping; Predictions; and Conclusions. The section on Tables, graphs, and statistics details the appropriate use of the following methods to summarize data: contingency tables, summary tables, graphs, descriptive statistics, hypothesis statistics, and correlation statistics. The Grouping section discusses the background of how and why grouping is necessary. A series of technical sections is provided and describes varied grouping approaches. The following techniques are discussed in detail: association rules, decision trees, and agglomerative hierarchical clustering. The Prediction section describes the steps and issues that need to be thought through when developing a model for making predictions. A number of technical topics are discussed in detail, such as linear regressions, neural networks, and k-nearest neighbors.
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