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Comparative Approaches to Using R and Python for Statistical Data Analysis

Comparative Approaches to Using R and Python for Statistical Data Analysis

Rui Sarmento (University of Porto, Portugal) and Vera Costa (University of Porto, Portugal)
Copyright: © 2017 |Pages: 197
ISBN13: 9781683180166|ISBN10: 168318016X|EISBN13: 9781522519898
DOI: 10.4018/978-1-68318-016-6
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MLA

Sarmento, Rui and Vera Costa. Comparative Approaches to Using R and Python for Statistical Data Analysis. IGI Global, 2017. http://doi:10.4018/978-1-68318-016-6

APA

Sarmento, R., & Costa, V. (2017). Comparative Approaches to Using R and Python for Statistical Data Analysis. IGI Global. http://doi:10.4018/978-1-68318-016-6

Chicago

Sarmento, Rui, and Vera Costa. Comparative Approaches to Using R and Python for Statistical Data Analysis. Hershey, PA: IGI Global, 2017. http://doi:10.4018/978-1-68318-016-6

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The application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users.

Comparative Approaches to Using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis.

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Table of Contents

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Front Materials
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Title Page
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Copyright Page
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Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) Book Series
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Dedication
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Preface
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Introduction
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Chapters
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Chapter 1
Statistics  (pages 1-31)
Statistics is a set of methods used to analyze data. This chapter presents the main concepts used in statistics, learning from data is one of the most critical challenges. In general, we can say that statistic based on the theory of...
Statistics
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Chapter 2
This chapter introduces the basic concepts of the languages we propose to use in the data analysis tasks. Thus, we first introduce some features of R and Python.
Introduction to Programming R and Python Languages
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Chapter 3
Dataset  (pages 78-82)
In this chapter, we present the dataset used in the course of this book. Our case study is built upon fictional data. This process implied “collecting” data, and we will explain each of the chosen variables with more detail.
Dataset
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Chapter 4
Descriptive Analysis  (pages 83-113)
Descriptive statistics is the initial stage of analysis used to describe and summarize data. The availability of a large amount of data and very efficient computational methods strengthened this area of the statistic. In this...
Descriptive Analysis
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Chapter 5
Statistical Inference  (pages 114-139)
Statistical inference allows drawing conclusions from data. These analyses use a random sample of data taken from a population to describe and make inferences about the population. Inferential statistics are valuable when it is not...
Statistical Inference
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Chapter 6
In statistical modelling, regression analysis is a statistical process for estimating the relationships among variables. More specifically, regression analysis helps the reader understand how the dependent variable changes when any...
Introduction to Linear Regression
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Chapter 7
Factor Analysis  (pages 148-178)
Factor analysis is a statistical method used to describe variability among observed, correlated variables. The goal of performing factor analysis is to search for some unobserved variables called factors. The observed variables are...
Factor Analysis
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Chapter 8
Clusters  (pages 179-190)
Cluster analysis, which we approach in this chapter, is the task of grouping a set of objects in such a way that objects in the same group or cluster are more similar to each other than to those in other groups or clusters. It is a...
Clusters
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Chapter 9
Discussion and Conclusion  (pages 191-194)
After all of the material we covered throughout this book, this chapter ends the book with a discussion and conclusion about the document's purpose. Thus, in this chapter, we try to clearly state the reasons why we have used the...
Discussion and Conclusion
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Back Materials
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About the Authors
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Index
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