Statistical Modeling: A Fresh Approach by Daniel Kaplan

Statistical Modeling: A Fresh Approach (Project MOSAIC Books)

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File Size: 5468 KB.
Print Length: 433 pages.
Language: English.
ASIN: B073WDBJ57.
Formats: PDF, ePUB & mobi.

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4.6 Stars (4.6 / 5) (13 votes).

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Statistical Modeling: A Fresh Approach (Project MOSAIC Books)

"Statistical Modeling: A Fresh Approach" introduces and illuminates the statistical reasoning used in modern research throughout the natural and social sciences, medicine, government, and commerce. It emphasizes the use of models to untangle and quantify variation in observed data. By a deft and concise use of computing coupled with an innovative geometrical presentation of the relationship among variables, "A Fresh Approach" reveals the logic of statistical inference and empowers the reader to use and understand techniques such as analysis of covariance that appear widely in published research but are hardly ever found in introductory texts.

Recognizing the essential role the computer plays in modern statistics, "A Fresh Approach" provides a complete and self-contained introduction to statistical computing using the powerful (and free) statistics package R.

Project MOSAIC is a collaboration to strengthen connections between modeling, statistics, and computation in the undergraduate mathematics curriculum.

Exercises, tutorials, and other materials to support for the book are available at http://www.mosaic-web.org/StatisticalModeling.

The author, Daniel Kaplan, is DeWitt Wallace Professor of Mathematics, Statistics, and Computer Science at Macalester College. A winner of Macalester’s "Excellence in Teaching" award, he was also awarded the 2017 "Lifetime Achievement Award in Statistics Education" by the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE).

Other books by the author:
Understanding Nonlinear Dynamics
Introduction to Scientific Computation and Programming
Data Computing
Modern Data Science with R

Praise for "Statistical Modeling: A Fresh Approach" …

"If we statistician/teachers can follow this example of teaching modeling in a first stat course, in such an accessible, thoughtful, statistically sophisticated way, the consequences for the future of our profession could be profound." — Prof. George Cobb, Mount Holyoke College

"Brings a refreshing approach to data and statistics, laying a foundation for statistical modeling. The goal of modeling is immediately apparent: reliable answers and useful predictions. I am thankful that this textbook is available to my students."
— Prof. Roy Henk, Kyoto University

"An outstandingly good introduction to statistics." — Dr. Geoff Smith, MBE, University of Bath

"We’ve been hearing a lot recently about the need to incorporate much more realistic and complicated statistical models into our introductory statistics courses. This book does that and more, with appropriate computing support in R and lots of interesting and sophisticated models. — Prof. Nicholas Horton, Amherst College

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