Introduction to R

Format:

Book

Language:

English

Subjects (All):

Social sciences.

Physical Description:

Online course : (20 hr.)

Place of Publication:

London : SAGE Publishing 2020

Summary:

This course teaches learners the required skills to use this flexible and multi-purpose platform for their own research. This course will help learners to: •Have a good understanding of how R works. •Be able to perform a wide range of data management tasks, with a focus on solving day-to-day conundrums that we all face as social scientists. •Have the knowledge and skills to apply an extensive set of data exploratory and visualization techniques. •Be able to use R to perform some of the most common statistical techniques used in the social sciences, namely a dimension reduction technique and OLS regression with interactions. MODULE ONE: WHAT IS R AND WHY USE IT? 1. About the course and author 2. What is R? 3. Installing R 4. Installing and exploring RStudio 5. Resources, Repositories and Events MODULE TWO: THE R LANGUAGE SIMPLIFIED 1. Introduction 2. Objects and functions 3. Installing packages and help 4. Vectors, lists and factors 5. Organizing R scripts 6. R Environments and Workspace MODULE THREE: EVERYDAY DATA MANAGEMENT 1.Introduction 2. Creating data in R 3. Importing and exporting data 4. Merging and cleaning data MODULE FOUR: DESCRIPTIVE STATISTICS AND GRAPHS 1.Introduction 2. Measures of central tendency 3. Measures of dispersion 4. Examining the internal structure of an R object 5. Bar plots 6. Histograms 7. Scatter plot MODULE FIVE: SUMMATED SCALES IN R 1.Introduction 2. Loading the data set 3. Attitudes to immigration in GSS 2014 4. Data management 5. Summated scales 6. Reliability analysis MODULE SIX: ORDINARY LEAST SQUARES REGRESSION 1. Introduction 2. Cleaning data and recoding variables 3. Bivariate regressions 4. Multivariate regression models 5. Fitting interactions terms 6. Visualizing interactions 7. Creating publication quality tables FINAL PROJECT 1. Introduction Data management 1: Importing data Data exploration 1 Data visualization 1: Histogram Data exploration 2 Data management 2: Recoding variables OLS Regression 1 OLS Regression 2 Data visualization 2: Interaction plot BIG DATA AND R IN BRIEF 1.Big Data and R in brief 2. End of our journey...

ISBN:

9780954612085

OCLC:

1200116872