Practical Guide for Data Analysis Using R Tool (eBook, PDF)
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Document from the year 2021 in the subject Economics - Statistics and Methods, grade: "-", , course: Independent Researcher, language: English, abstract: The purpose of this guide is to show how to conduct some data analysis using R tool. This guide is not aiming teaching statistics or related field, nevertheless, it shows practically when and how inferential statistics are conducted for those who have little knowledge on R programing environment. It is a collection of packages needed to conduct data analysis. The guide indicates step by step how to choose statistical test based on the researc...
Document from the year 2021 in the subject Economics - Statistics and Methods, grade: "-", , course: Independent Researcher, language: English, abstract: The purpose of this guide is to show how to conduct some data analysis using R tool. This guide is not aiming teaching statistics or related field, nevertheless, it shows practically when and how inferential statistics are conducted for those who have little knowledge on R programing environment. It is a collection of packages needed to conduct data analysis. The guide indicates step by step how to choose statistical test based on the research questions. It also presents the assumptions to be respected to validate a statistical test. This guide covers normality test, correlation analysis (numerical, ordinal, binary, & categorical), multiple regression analysis, robust regression, nonparametric regression, comparing one-sample mean to a standard known mean; comparing the means of two independent groups, comparing the means of paired samples, comparing the means of more than two group, independence test, comparing proportion, goodness of fit test, testing for stationarity for time series, exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. Scripts and codes are available for each test. It shows how to report the result of the analysis. This guide will help researchers and data analysts, and will contribute to increasing the quality of their publications.
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