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Regression analysis by example

By: Contributor(s): Material type: TextTextSeries: Wiley Series in Probability and StatisticsPublication details: New Jersey New Delhi 2014Edition: 5th edDescription: xv, 393 pISBN:
  • 9788126545667
Subject(s): DDC classification:
  • 519.536 C4R3-2014
Summary: Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The book now includes a new chapter on the detection and correction of multicollinearity, while also showcasing the use of the discussed methods on newly added data sets from the fields of engineering, medicine, and business. The Fifth Edition also explores additional topics, including:
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Item type Current library Item location Collection Shelving location Call number Status Notes Date due Barcode
Books Vikram Sarabhai Library Rack 28-B / Slot 1426 (0 Floor, East Wing) Non-fiction General Stacks 519.536 C4R3-2014 (Browse shelf(Opens below)) Available PM 181403

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression.

The book now includes a new chapter on the detection and correction of multicollinearity, while also showcasing the use of the discussed methods on newly added data sets from the fields of engineering, medicine, and business. The Fifth Edition also explores additional topics, including:

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