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Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
book

Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

by Glenn J. Myatt
November 2006
Beginner to intermediate
292 pages
7h 26m
English
Wiley-Interscience
Content preview from Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

3.7 FURTHER READING

This chapter has reviewed some of the sources of data used in exploratory data analysis and data mining. The following books provide more information on surveys and polls: Fowler (2002), Rea (2005), and Alreck (2004). There are many additional resources describing experimental design including Montgomery (2005), Cochran (1957), Barrentine (1999), and Antony (2003). Operational databases and data warehouses are summarized in the following books: Oppel (2004) and Kimball (2002). Oppel (2004) also summarizes access and manipulation of information in databases. Principal component analysis provides the opportunity to reduce the number of variables into a smaller set of principal components and is often used as a data reduction method. It is outlined in Jolliffe (2002) and Jackson (2003). For additional data preparation approaches including the handling of missing data see Pearson (2005), Pyle (1999), and Dasu (2003).

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Publisher Resources

ISBN: 9780470074718Purchase book