Applied Univariate  Bivariate  and Multivariate Statistics Using Python Book PDF

Applied Univariate Bivariate and Multivariate Statistics Using Python

  • Author : Daniel J. Denis
  • Publisher : John Wiley & Sons
  • Release Date : 2021-05-11
  • Genre : Mathematics
  • Pages : 304
  • ISBN : 9781119578147

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Applied Univariate Bivariate and Multivariate Statistics Using Python Book Description :

Applied Univariate, Bivariate, and Multivariate Statistics Using Python A practical, “how-to” reference for anyone performing essential statistical analyses and data management tasks in Python Applied Univariate, Bivariate, and Multivariate Statistics Using Python delivers a comprehensive introduction to a wide range of statistical methods performed using Python in a single, one-stop reference. The book contains user-friendly guidance and instructions on using Python to run a variety of statistical procedures without getting bogged down in unnecessary theory. Throughout, the author emphasizes a set of computational tools used in the discovery of empirical patterns, as well as several popular statistical analyses and data management tasks that can be immediately applied. Most of the datasets used in the book are small enough to be easily entered into Python manually, though they can also be downloaded for free from www.datapsyc.com. Only minimal knowledge of statistics is assumed, making the book perfect for those seeking an easily accessible toolkit for statistical analysis with Python. Applied Univariate, Bivariate, and Multivariate Statistics Using Python represents the fastest way to learn how to analyze data with Python. Readers will also benefit from the inclusion of: A review of essential statistical principles, including types of data, measurement, significance tests, significance levels, and type I and type II errors An introduction to Python, exploring how to communicate with Python A treatment of exploratory data analysis, basic statistics and visual displays, including frequencies and descriptives, q-q plots, box-and-whisker plots, and data management An introduction to topics such as ANOVA, MANOVA and discriminant analysis, regression, principal components analysis, factor analysis, cluster analysis, among others, exploring the nature of what these techniques can vs. cannot do on a methodological level Perfect for undergraduate and graduate students

Applied Univariate  Bivariate  and Multivariate Statistics Using Python Book PDF

Applied Univariate Bivariate and Multivariate Statistics Using Python

  • Author : Daniel J. Denis
  • Publisher : John Wiley & Sons
  • Release Date : 2021-07-14
  • Genre : Mathematics
  • Pages : 304
  • ISBN : 9781119578185

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Applied Univariate Bivariate and Multivariate Statistics Using Python Book Description :

Applied Univariate, Bivariate, and Multivariate Statistics Using Python A practical, “how-to” reference for anyone performing essential statistical analyses and data management tasks in Python Applied Univariate, Bivariate, and Multivariate Statistics Using Python delivers a comprehensive introduction to a wide range of statistical methods performed using Python in a single, one-stop reference. The book contains user-friendly guidance and instructions on using Python to run a variety of statistical procedures without getting bogged down in unnecessary theory. Throughout, the author emphasizes a set of computational tools used in the discovery of empirical patterns, as well as several popular statistical analyses and data management tasks that can be immediately applied. Most of the datasets used in the book are small enough to be easily entered into Python manually, though they can also be downloaded for free from www.datapsyc.com. Only minimal knowledge of statistics is assumed, making the book perfect for those seeking an easily accessible toolkit for statistical analysis with Python. Applied Univariate, Bivariate, and Multivariate Statistics Using Python represents the fastest way to learn how to analyze data with Python. Readers will also benefit from the inclusion of: A review of essential statistical principles, including types of data, measurement, significance tests, significance levels, and type I and type II errors An introduction to Python, exploring how to communicate with Python A treatment of exploratory data analysis, basic statistics and visual displays, including frequencies and descriptives, q-q plots, box-and-whisker plots, and data management An introduction to topics such as ANOVA, MANOVA and discriminant analysis, regression, principal components analysis, factor analysis, cluster analysis, among others, exploring the nature of what these techniques can vs. cannot do on a methodological level Perfect for undergraduate and graduate students

Univariate  Bivariate  and Multivariate Statistics Using R Book PDF

Univariate Bivariate and Multivariate Statistics Using R

  • Author : Daniel J. Denis
  • Publisher : John Wiley & Sons
  • Release Date : 2020-04-14
  • Genre : Mathematics
  • Pages : 384
  • ISBN : 9781119549932

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Univariate Bivariate and Multivariate Statistics Using R Book Description :

A practical source for performing essential statistical analyses and data management tasks in R Univariate, Bivariate, and Multivariate Statistics Using R offers a practical and very user-friendly introduction to the use of R software that covers a range of statistical methods featured in data analysis and data science. The author— a noted expert in quantitative teaching —has written a quick go-to reference for performing essential statistical analyses and data management tasks in R. Requiring only minimal prior knowledge, the book introduces concepts needed for an immediate yet clear understanding of statistical concepts essential to interpreting software output. The author explores univariate, bivariate, and multivariate statistical methods, as well as select nonparametric tests. Altogether a hands-on manual on the applied statistics and essential R computing capabilities needed to write theses, dissertations, as well as research publications. The book is comprehensive in its coverage of univariate through to multivariate procedures, while serving as a friendly and gentle introduction to R software for the newcomer. This important resource: Offers an introductory, concise guide to the computational tools that are useful for making sense out of data using R statistical software Provides a resource for students and professionals in the social, behavioral, and natural sciences Puts the emphasis on the computational tools used in the discovery of empirical patterns Features a variety of popular statistical analyses and data management tasks that can be immediately and quickly applied as needed to research projects Shows how to apply statistical analysis using R to data sets in order to get started quickly performing essential tasks in data analysis and data science Written for students, professionals, and researchers primarily in the social, behavioral, and natural sciences, Univariate, Bivariate, and Multivariate Statistics Using R offers an easy-to-use guide for

Using Geochemical Data Book PDF

Using Geochemical Data

  • Author : Hugh Rollinson
  • Publisher : Cambridge University Press
  • Release Date : 2021-05-06
  • Genre : Science
  • Pages : 231
  • ISBN : 9781108803823

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Using Geochemical Data Book Description :

This textbook is a complete rewrite, and expansion of Hugh Rollinson's highly successful 1993 book Using Geochemical Data: Evaluation, Presentation, Interpretation. Rollinson and Pease's new book covers the explosion in geochemical thinking over the past three decades, as new instruments and techniques have come online. It provides a comprehensive overview of how modern geochemical data are used in the understanding of geological and petrological processes. It covers major element, trace element, and radiogenic and stable isotope geochemistry. It explains the potential of many geochemical techniques, provides examples of their application, and emphasizes how to interpret the resulting data. Additional topics covered include the critical statistical analysis of geochemical data, current geochemical techniques, effective display of geochemical data, and the application of data in problem solving and identifying petrogenetic processes within a geological context. It will be invaluable for all graduate students, researchers, and professionals using geochemical techniques.

Mining Imperfect Data Book PDF

Mining Imperfect Data

  • Author : Ronald K. Pearson
  • Publisher : SIAM
  • Release Date : 2005-04-01
  • Genre : Computers
  • Pages : 312
  • ISBN : 9780898715828

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Mining Imperfect Data Book Description :

This book discusses the problems that can occur in data mining, including their sources, consequences, detection and treatment.

The Skew Normal and Related Families Book PDF

The Skew Normal and Related Families

  • Author : Adelchi Azzalini
  • Publisher : Cambridge University Press
  • Release Date : 2013-12-19
  • Genre : Business & Economics
  • Pages : 270
  • ISBN : 9781107029279

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The Skew Normal and Related Families Book Description :

The standard resource for statisticians and applied researchers. Accessible to the wide range of researchers who use statistical modelling techniques.