Магистратура
2022/2023
Количественный анализ данных в R
Статус:
Курс обязательный (Сравнительные социальные исследования / Comparative Social Research)
Направление:
39.04.01. Социология
Кто читает:
Департамент социологии
Где читается:
Факультет социальных наук
Когда читается:
1-й курс, 1-3 модуль
Формат изучения:
с онлайн-курсом
Онлайн-часы:
20
Охват аудитории:
для всех кампусов НИУ ВШЭ
Прогр. обучения:
Сравнительные социальные исследования
Язык:
английский
Кредиты:
9
Контактные часы:
100
Course Syllabus
Abstract
The course aims to provide students with an understanding of the key concepts and methods of modern statistical data analysis. It gives an overview of the skills necessary for conducting social research with quantitative survey data using R software. The course covers basic statistics, t-tests, one-way ANOVA, Pearson's chi-square, correlations and regression analysis. It also puts these skills into the broader academic context by reviewing how data analysis is used in real research practice. This course includes an online course " Introduction to Statistics" provided by Stepik (https://stepik.org/course/701/promo?search=954698307).
This course consists of 3 parts:
1. Introduction into quantitative research design (1st module).
2. Introduction into R and basic statistics (2nd module).
3. Quantitative data analysis using R (3rd module).
Learning Objectives
- Provide students with an understanding of the key principles of quantitative research and methods of modern statistical data analysis
Expected Learning Outcomes
- Have skills in interpreting results and writing research papers
- Have skills in the evaluation of the quality of published research papers
- Have skills in using R Studio for statistical data analysis
- Know the academic standards of reporting results and professional scientific ethics
- know the key concepts of statistics
- know the main methods and techniques of statistical data analysis
- To be able to analyze secondary data at the level required for an MA thesis
- to be able to interpret and present the results of data analysis in oral and written form
- 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
- Introduction into R
- Introduction into sociological inquiry
- Measurement
- Data transformations
- Descriptive statistics
- Visualization
- Statistical inference in social sciences
- T-tests, One-way ANOVA
- Non-parametric analogues of T-tests and one-way ANOVA
- Pearson's chi-square for contingency tables
- Correlations
- Linear regression
- Regression diagnostics: heteroscedasticity, multicollinearity, non-linearity
- Categorical independent variables in linear regression and interaction effects
- Binary logistic regression
Interim Assessment
- 2022/2023 2nd module0.11 * Reading published research + 0.2 * Home assignment + 0.29 * Essay + 0.11 * Test + 0.29 * Exam
- 2022/2023 3rd module0.11 * Test + 0.2 * Home assignment + 0.29 * Essay + 0.11 * Reading published research + 0.29 * Exam
Bibliography
Recommended Core Bibliography
- Adventures in social research : data analysis using IBM SPSS Statistics, Babbie, E., 2013
- An introduction to R : a programming environment for data analysis and graphics, Venables, W. N., 2009
- Applied missing data analysis, Enders, C. K., 2010
- Applied multivariate data analysis, Everitt, B. S., 2001
- Basic statistic for social research, Hanneman, R. A., 2013
- Categorical data analysis, Agresti, A., 2002
- 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
- ggplot2 : elegant graphics for data analysis, Wickham, H., 2009
- Introduction to social research, Babbie, E., 2011
- R in action : Data analysis and graphics with R, Kabacoff, R. I., 2011
- Statistics : a tool for social research, Healey, J. F., 2012
- The basics of social research, Babbie, E., 2014
- The essentials of statistics : a tool for social research, Healey, J. F., 2007
- The practice of social research, Babbie, E., 2013
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
- Mirkin, B. Core concepts in data analysis: summarization, correlation and visualization. – Springer Science & Business Media, 2011. – 388 pp.
- Wickham H. ggplot2: elegant graphics for data analysis. Second edition. Cham: Springer, 2016. 260 p.