The author clearly explains all the theory students will need to avoid mistakes, understand what regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples.
The author clearly explains all the theory students will need to avoid mistakes, understand what regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Conrad Carlberg (www.conradcarlberg.com) is a nationally recognized expert on Quantitative analysis and on data analysis and management applications such as Microsoft Excel, SAS, and Oracle. He holds a Ph.D. in statistics from the University of Colorado and is a many-time recipient of Microsoft’s Excel MVP designation. Carlberg is a Southern California native. After college he moved to Colorado, where he worked for a succession of startups and attended graduate school. He spent two years in the Middle East, teaching computer science and dodging surly camels. After finishing graduate school, Carlberg worked at US West (a Baby Bell) in product management and at Motorola. In 1995 he started a small consulting business that provides design and analysis services to companies that want to guide their business decisions by means of quantitative analysis—approaches that today we group under the term “analytics.” He enjoys writing about those techniques and, in particular, how to carry them out using the world’s most popular numeric analysis application, Microsoft Excel.
Inhaltsangabe
1 Measuring Variation: How Values Differ 2 Correlation 3 Simple Regression 4 Using the LINEST( ) Function 5 Multiple Regression 6 Assumptions and Cautions Regarding Regression Analysis 7 Using Regression to Test Differences Between Group Means
1 Measuring Variation: How Values Differ 2 Correlation 3 Simple Regression 4 Using the LINEST( ) Function 5 Multiple Regression 6 Assumptions and Cautions Regarding Regression Analysis 7 Using Regression to Test Differences Between Group Means
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