Applied multivariate statistical concepts

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This book covers the classic and cutting edge multivariate techniques used in today's research. Through using examples with real data, the book walks readers through the most used methods to learn why and how to apply each technique.

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Title Statements

Full title :Applied multivariate statistical concepts / by Debbie Hahs-Vaughn.

Summary

Edition Statements

Publication Date:2017.

Publication Statements

Publisher(s):Routledge
Place of Publication:New York, NY
Language:eng
Publication Date:2017.

Notes

Includes index.

The Physical Object

Description:pages cm

Edition Identifiers

ISBN:9780415842365, 0415842360, 9780415842358, 0415842352
oclc:ocn987618897
LC Classification:QA278
Dewey Decimal:519.5/35

Machine generated contents note: 1. Multivariate Statistics -- 1.1. What Are Multivariate Statistics? -- 1.2. Decision Rules -- 1.3. Coverage of the Textbook -- 1.4. Layout of the Textbook -- 1.5. Overarching Goal of the Textbook -- 2. Univariate and Bivariate Statistics Review -- 2.1. Fundamental Concepts -- 2.2. Foundational Univariate Statistics -- 2.3. Foundational Bivariate Statistics -- 3. Data Screening -- 3.1. Independence -- 3.2. Variance -- 3.3. Normality -- 3.4. Linearity -- 3.5. Noncollinearity -- 4. Multiple Linear Regression -- 4.1. What Multiple Linear Regression Is and How It Works -- 4.2. Mathematical Introduction Snapshot -- 4.3.Computing Multiple Linear Regression Using SPSS -- 4.4. Data Screening -- 4.5. Power Using G*Power -- 4.6. Research Question Template and Example Write-Up -- 5. Logistic Regression -- 5.1. What Logistic Regression Is and How It Works -- 5.2. Mathematical Introduction Snapshot -- 5.3.Computing Logistic Regression Using SPSS -- 5.4. Data Screening.

Note continued: 5.5. Power Using G*Power -- 5.6. Research Question Template and Example Write-Up -- 6. Multivariate Analysis of Variance: Single Factor, Factorial, and Repeated Measures Designs …