• Welcome
    • Description
    • Structure
    • Timetable and key locations
    • Contact details
  • Recommended Reading List
    • Week 1: Understanding Data
    • Week 2: Examining Data I
    • Week 3: Examining Data II
    • Week 4: Sourcing Data
    • Extra notes
  • 1 Understanding Data
    • 1.1 Introduction
    • 1.2 Instructions for accessing RStudio on UCL Server
    • 1.3 The environment in RStudio
    • 1.4 Using the R-Console as a calculator
    • 1.5 Creating basic objects and assigning values to them
    • 1.6 Data entry in RStudio
    • 1.7 Uploading data to RStudio Server and importing data into the environment
    • 1.8 Working with data in RStudio
      • 1.8.1 Useful functions
      • 1.8.2 Basic subsetting and manipulation of data
      • 1.8.3 Basic visualisation
      • 1.8.4 Frequency Distributions
    • 1.9 Seminar tasks and questions
  • 2 Examining data I
    • 2.1 Introduction
    • 2.2 Measures of central tendency
      • 2.2.1 Accessing RStudio Server, uploading and importing data
      • 2.2.2 Mean, Median and Mode
    • 2.3 Simple plots
    • 2.4 Measures of dispersion
    • 2.5 Seminar task & questions
  • 3 Examining data II
    • 3.1 Introduction
    • 3.2 Data visualisation
    • 3.3 ggplot2
    • 3.4 Seminar
    • 3.5 Before you leave
  • 4 Sourcing data
    • 4.1 Introduction
    • 4.2 Sourcing data
    • 4.3 Preparing data
    • 4.4 Seminar

POLS0008: Introduction to Quantitative Research Methods 2023/24

Recommended Reading List

Click this shared [LINK] to get access to these R books if you are having problems securing one or any from the UCL library or elsewhere.

Week 1: Understanding Data

  1. Book: [Theory, Basics] Cetinkaya-Rundel, M., and Hardin, J., 2021, Introduction to Modern Statistics, Section I: Introduction to data, Chapter 1: Hello data, Page(s): 12-22. Source: openintro.org/book/ims.

  2. Book: [R-programming, Basics] Dalgaard, P., 2008, Introductory Statistics with R, Chapter 1: Basics, Page(s): 1-28.

  3. Book: [R-programming, Data Management, Basics] Zuur, A.F., Ieno, E.N., & Meesters, E.H.W.G., 2008, A Beginner’s Guide to R, Chapter 2: Getting Data into R, Page(s): 29-54.

  4. Book: [R-programming, Data Management, Basics] Zuur, A.F., Ieno, E.N., & Meesters, E.H.W.G., 2009, A Beginner’s Guide to R, Chapter 3: Accessing Variables and Managing Subsets of Data, Page(s): 57-74.

Week 2: Examining Data I

  1. Book: [Theory, Basics] Cetinkaya-Rundel, M., and Hardin, J., 2021, Introduction to Modern Statistics, Section II: Exploratory data analysis, Chapter 5: Exploring numerical data, Page(s): 76-95. Source: openintro.org/book/ims.

  2. Book: [R-programming, Basics] Dalgaard, P., 2008, Introductory Statistics with R, Chapter 2: Descriptive statistics and graphics, Page(s): 67-93.

  3. Book: [R-programming, Data Management, Basics] Zuur, A.F., Ieno, E.N., & Meesters, E.H.W.G., 2008, A Beginner’s Guide to R, Chapter 2: Getting Data into R, Page(s): 29-54.

  4. Book: [R-programming, Data Management, Basics] Zuur, A.F., Ieno, E.N., & Meesters, E.H.W.G., 2009, A Beginner’s Guide to R, Chapter 3: Accessing Variables and Managing Subsets of Data, Page(s): 57-74.

  5. Book: [R-programming, Generating Graphs, Basics] Zuur, A.F., Ieno, E.N., & Meesters, E.H.W.G., 2009, A Beginner’s Guide to R, Chapter 7: Graphing Tools, Page(s): 127-167.

Week 3: Examining Data II

  1. Book: [R-programming (Base-R code), Generating Graphs, Basics] Zuur, A.F., Ieno, E.N., & Meesters, E.H.W.G., 2009, A Beginner’s Guide to R, Chapter 7: Graphing Tools, Page(s): 127-167.

  2. Book: [R-programming (Base-R code), Basics, Visualisation] Dalgaard, P., 2008, Introductory Statistics with R, Chapter 2: Descriptive statistics and graphics, Page(s): 67-93.

  3. Book: [R-programming (Tidyverse code), Basics, Visualisation] Wickham, H., and Grolemund, G., 2017, R for Data Science, Chapter 1: Data visualisation with ggplot2, Page(s): 3-33.

  4. Book: [Theory, Basics, Graphics] Cetinkaya-Rundel, M., and Hardin, J., 2021, Introduction to Modern Statistics, Section II: Exploratory data analysis, Chapter 4: Exploring categorical data, Page(s): 61-74. Source: openintro.org/book/ims.

  5. Book: [Theory, Basics, Graphics] Cetinkaya-Rundel, M., and Hardin, J., 2021, Introduction to Modern Statistics, Section II: Exploratory data analysis, Chapter 5: Exploring numerical data, Page(s): 76-95. Source: openintro.org/book/ims.

Week 4: Sourcing Data

  1. Article: [R-programming (Tidyverse code), Data Management] Wickham, 2014, Tidy data, Journal of Statistical Software 59(10). [Link]

  2. Book: [R-programming (Tidyverse code), Basics, Data Management] Wickham, H., and Grolemund, G., 2017, R for Data Science, Chapter 3: Data Transformation with dplyr, Page(s): 43-73.

  3. Book: [R-programming (Tidyverse code), Basics, Data Management] Wickham, H., and Grolemund, G., 2017, R for Data Science, Chapter 9: Tidy Data with tidyr, Page(s): 147-168.

Extra notes

  • For other reading materials beyond what’s mentioned here please read through the Module Outline document [HERE] which also is accessible on Moodle.

  • To follow the examples with the dataset provided in the book “Introductory Statistics with R”. You will need to install a package called “ISwR”. Here is the code chuck for performing such installation.

# install the ISwR using install.packages() function
install.packages("ISwR")
# active it using library() function
library("ISwR")
# this should allow to use the datasets ‘thuesen’ and ‘eba1977’ to follow the examples in book
# to add data - use the data() function
data("thuesen")
data("eba1977")
# see the datasets
thuesen
eba1977