Share

Applied Univariate, Bivariate, and Multivariate Statistics Using Python

2021-05-11 Mathematics
Download Applied Univariate, Bivariate, and Multivariate Statistics Using Python PDF Online Free

Author :
Release : 2021-05-11
Genre : Mathematics
Kind : eBook
Book Rating : 140/5 ( reviews)

GET EBOOK


Book Synopsis Applied Univariate, Bivariate, and Multivariate Statistics Using Python by : Daniel J. Denis

Download or read book Applied Univariate, Bivariate, and Multivariate Statistics Using Python written by Daniel J. Denis. This book was released on 2021-05-11. Available in PDF, EPUB and Kindle. Book excerpt: 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 in the social, behavioral, and natural sciences, Applied Univariate, Bivariate, and Multivariate Statistics Using Python will also earn a place in the libraries of researchers and data analysts seeking a quick go-to resource for univariate, bivariate, and multivariate analysis in Python.

Applied Univariate, Bivariate, and Multivariate Statistics

2015-11-02 Mathematics
Download Applied Univariate, Bivariate, and Multivariate Statistics PDF Online Free

Author :
Release : 2015-11-02
Genre : Mathematics
Kind : eBook
Book Rating : 311/5 ( reviews)

GET EBOOK


Book Synopsis Applied Univariate, Bivariate, and Multivariate Statistics by : Daniel J. Denis

Download or read book Applied Univariate, Bivariate, and Multivariate Statistics written by Daniel J. Denis. This book was released on 2015-11-02. Available in PDF, EPUB and Kindle. Book excerpt: A clear and efficient balance between theory and application of statistical modeling techniques in the social and behavioral sciences Written as a general and accessible introduction, Applied Univariate, Bivariate, and Multivariate Statistics provides an overview of statistical modeling techniques used in fields in the social and behavioral sciences. Blending statistical theory and methodology, the book surveys both the technical and theoretical aspects of good data analysis. Featuring applied resources at various levels, the book includes statistical techniques such as t-tests and correlation as well as more advanced procedures such as MANOVA, factor analysis, and structural equation modeling. To promote a more in-depth interpretation of statistical techniques across the sciences, the book surveys some of the technical arguments underlying formulas and equations. Applied Univariate, Bivariate, and Multivariate Statistics also features Demonstrations of statistical techniques using software packages such as R and SPSS® Examples of hypothetical and real data with subsequent statistical analyses Historical and philosophical insights into many of the techniques used in modern social science A companion website that includes further instructional details, additional data sets, solutions to selected exercises, and multiple programming options An ideal textbook for courses in statistics and methodology at the upper- undergraduate and graduate-levels in psychology, political science, biology, sociology, education, economics, communications, law, and survey research, Applied Univariate, Bivariate, and Multivariate Statistics is also a useful reference for practitioners and researchers in their field of application. DANIEL J. DENIS, PhD, is Associate Professor of Quantitative Psychology at the University of Montana where he teaches courses in univariate and multivariate statistics. He has published a number of articles in peer-reviewed journals and has served as consultant to researchers and practitioners in a variety of fields.

Computer Science in Sport

Download Computer Science in Sport PDF Online Free

Author :
Release :
Genre :
Kind : eBook
Book Rating : 13X/5 ( reviews)

GET EBOOK


Book Synopsis Computer Science in Sport by : Daniel Memmert

Download or read book Computer Science in Sport written by Daniel Memmert. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:

SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics

2018-09-25 Mathematics
Download SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics PDF Online Free

Author :
Release : 2018-09-25
Genre : Mathematics
Kind : eBook
Book Rating : 818/5 ( reviews)

GET EBOOK


Book Synopsis SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics by : Daniel J. Denis

Download or read book SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics written by Daniel J. Denis. This book was released on 2018-09-25. Available in PDF, EPUB and Kindle. Book excerpt: Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks.

Exploratory Data Analysis with Python Cookbook

2023-06-23
Download Exploratory Data Analysis with Python Cookbook PDF Online Free

Author :
Release : 2023-06-23
Genre :
Kind : eBook
Book Rating : 105/5 ( reviews)

GET EBOOK


Book Synopsis Exploratory Data Analysis with Python Cookbook by : Ayodele Oluleye

Download or read book Exploratory Data Analysis with Python Cookbook written by Ayodele Oluleye. This book was released on 2023-06-23. Available in PDF, EPUB and Kindle. Book excerpt: Extract valuable insights from data by leveraging various analysis and visualization techniques with this comprehensive guide Purchase of the print or Kindle book includes a free PDF eBook Key Features: Gain practical experience in conducting EDA on a single variable of interest in Python Learn the different techniques for analyzing and exploring tabular, time series, and textual data in Python Get well versed in data visualization using leading Python libraries like Matplotlib and seaborn Book Description: Exploratory data analysis (EDA) is a crucial step in data analysis and machine learning projects as it helps in uncovering relationships and patterns and provides insights into structured and unstructured datasets. With various techniques and libraries available for performing EDA, choosing the right approach can sometimes be challenging. This hands-on guide provides you with practical steps and ready-to-use code for conducting exploratory analysis on tabular, time series, and textual data. The book begins by focusing on preliminary recipes such as summary statistics, data preparation, and data visualization libraries. As you advance, you'll discover how to implement univariate, bivariate, and multivariate analyses on tabular data. Throughout the chapters, you'll become well versed in popular Python visualization and data manipulation libraries such as seaborn and pandas. By the end of this book, you will have mastered the various EDA techniques and implemented them efficiently on structured and unstructured data. What You Will Learn: Perform EDA with leading Python data visualization libraries Execute univariate, bivariate, and multivariate analyses on tabular data Uncover patterns and relationships within time series data Identify hidden patterns within textual data Discover different techniques to prepare data for analysis Overcome the challenge of outliers and missing values during data analysis Leverage automated EDA for fast and efficient analysis Who this book is for: If you are a data analyst interested in the practical application of exploratory data analysis in Python, then this book is for you. This book will also benefit data scientists, researchers, and statisticians who are looking for hands-on instructions on how to apply EDA techniques using Python libraries. Basic knowledge of Python programming and a basic understanding of fundamental statistical concepts is a prerequisite.

You may also like...