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Regular version of the site
Master 2018/2019

Basic Statistics and Introduction into "R"

Type: Compulsory course (Comparative Social Research)
Area of studies: Sociology
Delivered by: School of Sociology
When: 1 year, 1 module
Mode of studies: Full time
Instructors: Anna Almakaeva
Master’s programme: Comparative Soсial Research
Language: English
ECTS credits: 2

Course Syllabus

Abstract

The course aims to provide students with an understanding of key concepts and methods of modern statistical data analysis. It gives an overview of the skills necessary for conducting independent research with quantitative survey data, using R software. The course also puts these skills into the broader academic context by reviewing how statistics are used in published scientific journal articles.
Learning Objectives

Learning Objectives

  • Provide students with an understanding of the basic concepts of statistical analysis
  • Provide students with an understanding of the basic principles of R programming
Expected Learning Outcomes

Expected Learning Outcomes

  • know the key concepts of basic statistics, main principles and procedures R programming, main procedures of data transformation and statistical analysis in R Studio.
  • be able to choose correct statistical methods and procedures according to the research questions and the level of measurement, read and transform data in R Studio, calculate basic statistics in R Studio, interpret and present results of in oral and written form
  • have skills in using R Studio for reading and transforming data, calculation of basic statistics and interpretation of results
Course Contents

Course Contents

  • Introduction into R
    Installing R and R Studio. Exploring R Studio space and windows. Reading and installing working directory. Installing packages. Getting help. Using R as a calculator. Types of objects and assigning objects. Creating vectors, matrixes, lists, data frames. Using package “foreign” and importing data frames. Attaching and detaching objects, indexing objects.
  • Measurement
    Definition of measurement. Levels of measurement/types of scales (nominal, ordinal, interval, ratio), properties. Examples of different scale types from famous cross-cultural studies (European Social Survey, World Values Survey, European Values Study). Possible mathematical transformations with different scale types. Most frequent mistakes in defining scale type. Indexing.
  • Introduction into sociological inquiry
    Two main research designs: qualitative and quantitative and their peculiar features. Stages of quantitative research. Possible units of analysis in quantitative research.
  • Data transformation
    Package “car”: installation, reading and most common problems. Inspecting data-sets, creating subsets. Creating new variables, scale reduction, scale normalization, creating indexes, changing variable type.
  • Descriptive statistics
    Calculating proportions, mean, mode, median (for odd and even scales), standard deviation and variance. Treating missing data in R. R functions for calculating basis statistics. Frequencies and cross-tables. Different ways of calculating proportions for cross-tables. Creating frequencies and cross-tables in R. Using package “stargazer” for exporting results
  • Visualization
    Basic graphs in R. Package ggplot2 and its opportunities for visualization.
Assessment Elements

Assessment Elements

  • non-blocking Home assignment
    Grading criteria:1) Correct method of data analysis. 2) Correct R function. 3) Correct interpretation.
  • non-blocking Reading previous research
  • non-blocking Essay
  • non-blocking Exam
    The task of the first reexam is similar to the first exam. Students will have 3 hours to do it. The second reexam is similar to the first one. The weight of the reexam in the final grade is 0.3.
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.3 * Essay + 0.3 * Exam + 0.2 * Home assignment + 0.2 * Reading previous research
Bibliography

Bibliography

Recommended Core Bibliography

  • Field, A. V. (DE-588)128714581, (DE-627)378310763, (DE-576)186310501, aut. (2012). Discovering statistics using R Andy Field, Jeremy Miles, Zoë Field. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.363067604
  • Hadley, W. (2016). Ggplot2 : Elegant Graphics for Data Analysis. New York, NY: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1175341

Recommended Additional Bibliography

  • Hatekar, N. (2010). Principles of Econometrics : An Introduction (using R). New Delhi, India: SAGE Publications India Pvt., Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=354910
  • Layder, D. (1998). Sociological Practice : Linking Theory and Social Research. London: SAGE Publications Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=775757