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SA106 - Introduction to STATA

Instructor Details

Instructor Photo

Oana Lup

Institution:
Central European University

Instructor Bio

Oana Lup is Visiting Professor in CEU's Department of Political Science.

Her research interests include public opinion, political attitudes and behaviour, stereotypes and prejudice, political communication, social networks, quantitative research methods, and deliberative democracy and practices.

Oana has worked in various international projects such as Comparative National Elections Project, CivicActive, PIREDEU, and InTune. Her work has appeared in the Swiss Political Science Review and International Journal of Public Opinion Research.


Course Dates and Times

Thursday 28 - Saturday 30 July

10:00-12:00 and 14:00-17:00

15 hours over 3 days

Prerequisite Knowledge

The participants to this course need to have an understanding of elementary statistics and basic knowledge of empirical research design. If you are unsure of your level of knowledge please get in touch with the instructor. No prior experience with STATA is required.

Short Outline

In this course you will learn how to use Stata for conducting basic types of statistical analysis. The course will walk you through the typical stages of a process of empirical data analysis, from getting the data, through arranging the data in the needed formats and visualizing them, to conducting different statistical analyses and reporting the results in formats required by professional journals.

Specifically, the course includes the following components:

  • getting familiar with the Stata working environment, creating and opening data sets
  • data management procedures
  • computing and reporting summary/descriptive statistics
  • graphical visualization
  • measures of association,  significance tests
  • conducting linear regression and reporting the results in formats required by professional journals
Long Course Outline

In this course you will learn how to use STATA for conducting basic types of statistical analysis. The course will walk you through the typical stages of a process of empirical data analysis, from getting the data, through arranging the data in the needed formats and visualizing them, to conducting different statistical analyses and reporting the results in formats required by professional journals.

The course gives the participants practical, hands-on training in the use of STATA for conducting statistical analysis through a mix of examples presented by the instructor and a set of applications and exercises that the participants will solve and discuss in the class.

Although the course will present the STATA commands for conducting different types of statistical analyses and will briefly discuss their results, it will not teach the statistical theory behind these statistical methods. For example, when showing the STATA commands for conducting linear regression analysis and their results we will not cover the assumptions of the linear regression or how coefficients are calculated, although we will briefly discuss how to read the main elements of the output generated. This assumes that the participants have some basic knowledge of statistics, although the interpretation of the results will be formulated in terms that appeal to the basic intuition behind these concepts.

The participants will also learn how to use the STATA manual and help menu for writing commands that they need for conducting various statistical analyses.

 

The list of topics that will be covered in the course includes:

 

  • Introduce the STATA working environment – graphic user interface (GUI), load data, set current working directory, help menu, do file, log file, commands to describe variables in data sets
  • Create a data set, save data set, save do files, log files
  • Data management: merge databases, keep and drop variables, recode variables, rename variables, create new variables, dummy variables, label variables, apply value labels to variables, add labels, drop labels, replace labels, sort observations, display missing values 
  • Summary/descriptive statistics – mean, median, mode, standard deviation, mean comparisons, distribution, min and max values, various qualifiers and operators for creating and summarizing variables, cross tables
  • Graphical visualization – creating various types of graphs for summarizing the data (histograms, pie charts, bar charts, scatter plots/two dimensional scatter plots, line plots), graph editing, exporting graphs
  • Measures of association – for nominal variables (crosstabs, chi2), for ordinal variables (Spearman’s Rho, odds ratio), interval variables (correlation)
  • Hypothesis testing: t-test (single sample test, paired, and independent t tests assuming equal and unequal variance)
  • Regressions: linear regression (command, results, estimate predicted values, interaction effects, plotting effects), save table results in journal format. Depending on the participants’ interest the course may also discuss other types of regressions, e.g. logistic, ordered logit.
Day-to-Day Schedule

Software Requirements

STATA 12

Hardware Requirements

None

Literature

Acock, Alan 2014. A Gentle Introduction to Stata, revised 4th ed. College Station, TX: Stata Press.

Pollock, Philip. 2015. A Stata Companion to Political Analysis 3rd ed.  Washington DC: CQ Press.

Additional Information

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed in due time.

Note from the Academic Convenors

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, contact the instructor before registering.


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