Exploratory And Descriptive Statistics
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Exploratory And Descriptive Statistics
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Author : Julie Scott Jones
language : en
Publisher: SAGE
Release Date : 2022-03-01
Exploratory And Descriptive Statistics written by Julie Scott Jones and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Social Science categories.
Nervous about statistics? This guide offers you a clear, straight to the point break down of exploratory and descriptive statistics and its potential. Anchored by lots of examples and exercises to enhance your learning, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
Exploratory Data Analysis In Business And Economics
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Author : Thomas Cleff
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-12
Exploratory Data Analysis In Business And Economics written by Thomas Cleff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-12 with Business & Economics categories.
In a world in which we are constantly surrounded by data, figures, and statistics, it is imperative to understand and to be able to use quantitative methods. Statistical models and methods are among the most important tools in economic analysis, decision-making and business planning. This textbook, “Exploratory Data Analysis in Business and Economics”, aims to familiarise students of economics and business as well as practitioners in firms with the basic principles, techniques, and applications of descriptive statistics and data analysis. Drawing on practical examples from business settings, it demonstrates the basic descriptive methods of univariate and bivariate analysis. The textbook covers a range of subject matter, from data collection and scaling to the presentation and univariate analysis of quantitative data, and also includes analytic procedures for assessing bivariate relationships. It does not confine itself to presenting descriptive statistics, but also addresses the use of computer programmes such as Excel, SPSS, and STATA, thus treating all of the topics typically covered in a university course on descriptive statistics. The German edition of this textbook is one of the “bestsellers” on the German market for literature in statistics.
Descriptive Statistics And Exploratory Analysis Of Data With Matlab
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Author : Karter J.
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2016-10-13
Descriptive Statistics And Exploratory Analysis Of Data With Matlab written by Karter J. and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-13 with categories.
The aim of this book is to introduce the reader to the techniques of descriptive statistics and exploratory data analysis..Statistics Toolbox provides algorithms and tools for organizing, analyzing, and modeling data. You can use regression or classification for predictive modeling, generate random numbers for Monte Carlo simulations, use statistical plots for exploratory data analysis, and perform hypothesis tests. For analyzing multidimensional data, Statistics Toolbox includes algorithms that let you identify key variables that impact your model with sequential feature selection, transform your data with principal component analysis, apply regularization and shrinkage, or use partial least-squares regression. Statistics Toolbox includes specialized data types for organizing and accessing heterogeneous data. Dataset arrays store numeric data, text, and metadata in a single data container. Built-in methods enable you to merge datasets using a common key (join), calculate summary statistics on grouped data, and convert between tall and wide data representations. Categorical arrays provide a memory-efficient data container for storing information drawn from a finite, discrete set of categories.
Exploratory Analysis Of Data And Descriptive Statistics With Matlab
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Author : G. Peck
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-10-31
Exploratory Analysis Of Data And Descriptive Statistics With Matlab written by G. Peck and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-31 with categories.
Statistics and Machine Learning Toolbox provides functions and apps to describe, analyze, and model data. You can use descriptive statistics and plots for exploratory data analysis, fit probability distributions to data, generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms let you draw inferences from data and build predictive models. For multidimensional data analysis, Statistics and Machine Learning Toolbox provides feature selection, stepwise regression, principal component analysis (PCA), regularization, and other dimensionality reduction methods that let you identify variables or features that impact your model. The toolbox provides supervised and unsupervised machine learning algorithms, including support vector machines (SVMs), boosted and bagged decision trees, k-nearest neighbor, k-means, k-medoids, hierarchical clustering, Gaussian mixture models, and hidden Markov models. Many of the statistics and machine learning algorithms can be used for computations on data sets that are too big to be stored in memory.. This book develops organizing data techniques, descriptive statistics, plots for exploratory data analysis, data visualization techniques and other exploratory techniques across examples using MATLAB.
Descriptive Statistics With R
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Author : CESAR PEREZ LOPEZ
language : en
Publisher: CESAR PEREZ
Release Date : 2022
Descriptive Statistics With R written by CESAR PEREZ LOPEZ and has been published by CESAR PEREZ this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Computers categories.
R is a programming language and environment for statistical and graphical analysis. It is a free software project widely used by the statistical community. R implements a multitude of commands and functions to work in the statistical field. Specifically, this book delves into the work with R in Descriptive Statistics. It incorporates the functions for initial data treatment, exploratory data analysis, statistical graphs, quantitative expression of distributions, measures of centralization, measures of dispersion and shape, correlation, covariance, linear regression model, logistic regression, probit model, and other topics of descriptive statistics. The chapters begin with brief methodological notes and incorporate a variety of examples and exercises solved with the R software.
Statistics And Data Analysis Through R
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Author : César Pérez López
language : en
Publisher: Independently Published
Release Date : 2020-11-08
Statistics And Data Analysis Through R written by César Pérez López and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-08 with categories.
This book focuses on the implementation of statistics and data analysis through R. It deals first with the Exploratory Data Analysis both numerically and graphically, which is always a technique prior to any other statistical analysis. Descriptive statistics and the calculation of probabilities are then developed. Subsequently, the multiple regression model is approached, focusing on the problems of its estimation and diagnosis. It also delves into the generalized linear models and the analysis of variance and covariance models. Dimension reduction techniques are also addressed with special emphasis on principal component analysis and factor analysis. Finally, the segmentation techniques related to hierarchical and non-hierarchical cluster analysis are presented.
Making Sense Of Data I
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Author : Glenn J. Myatt
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-02
Making Sense Of Data I written by Glenn J. Myatt and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-02 with Mathematics categories.
Praise for the First Edition “...a well-written book on data analysis and data mining that provides an excellent foundation...” —CHOICE “This is a must-read book for learning practical statistics and data analysis...” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available TraceisTM software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.
Illustrating Statistical Procedures Finding Meaning In Quantitative Data
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Author : Ray W. Cooksey
language : en
Publisher: Springer Nature
Release Date : 2020-05-14
Illustrating Statistical Procedures Finding Meaning In Quantitative Data written by Ray W. Cooksey and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-14 with Mathematics categories.
This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.
Translating Statistics To Make Decisions
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Author : Victoria Cox
language : en
Publisher: Apress
Release Date : 2017-03-10
Translating Statistics To Make Decisions written by Victoria Cox and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-10 with Business & Economics categories.
Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians—and also statisticians who present statistical reports to non-statisticians—must avoid if statistical results are to be correctly used for evidence-based business decision making. Victoria Cox, senior statistician at the United Kingdom’s Defence Science and Technology Laboratory (Dstl), distills the lessons of her long experience presenting the actionable results of complex statistical studies to users of widely varying statistical sophistication across many disciplines: from scientists, engineers, analysts, and information technologists to executives, military personnel, project managers, and officials across UK government departments, industry, academia, and international partners. The author shows how faulty statistical reasoning often undermines the utility of statistical results even among those with advanced technical training. Translating Statistics teaches statistically naive readers enough about statistical questions, methods, models, assumptions, and statements that they will be able to extract the practical message from statistical reports and better constrain what conclusions cannot be made from the results. To non-statisticians with some statistical training, this book offers brush-ups, reminders, and tips for the proper use of statistics and solutions to common errors. To fellow statisticians, the author demonstrates how to present statistical output to non-statisticians to ensure that the statistical results are correctly understood and properly applied to real-world tasks and decisions. The book avoids algebra and proofs, but it does supply code written in R for those readers who are motivated to work out examples. Pointing along the way to instructive examples of statistics gone awry, Translating Statistics walks readers through the typical course of a statistical study, progressing from the experimental design stage through the data collection process, exploratory data analysis, descriptive statistics, uncertainty, hypothesis testing, statistical modelling and multivariate methods, to graphs suitable for final presentation. The steady focus throughout the book is on how to turn the mathematical artefacts and specialist jargon that are second nature to statisticians into plain English for corporate customers and stakeholders. The final chapter neatly summarizes the book’s lessons and insights for accurately communicating statistical reports to the non-statisticians who commission and act on them. What You'll Learn Recognize and avoid common errors and misconceptions that cause statistical studies to be misinterpreted and misused by non-statisticians in organizational settings Gain a practical understanding of the methods, processes, capabilities, and caveats of statistical studies to improve the application of statistical data to business decisions See how to code statistical solutions in R Who This Book Is For Non-statisticians—including both those with and without an introductory statistics course under their belts—who consume statistical reports in organizational settings, and statisticians who seek guidance for reporting statistical studies to non-statisticians in ways that will be accurately understood and will inform sound business and technical decisions
Analysis Of Symbolic Data
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Author : Hans-Hermann Bock
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Analysis Of Symbolic Data written by Hans-Hermann Bock and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This book presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.