2018 Stata Winter School, London

Our fourth annual Stata Winter School comprises a series of four separate short courses that allows the flexibility to attend one, a combination of or all courses consecutively.

The courses forming the 2018 Stata Winter School are:

  • Course 1: An introduction to Stata and data management (2-days)
  • Course 2: Data visualisation through Stata
  • Course 3: Analysing panel data in Stata (2-days)
  • Course 4: Visualising Regression Models Using Stata

Course 1: Introduction to Stata & Data Management (2-days)

10 & 11 December 2018

Course Overview

This two-day course assumes no or little prior experience with Stata. We therefore start right at the beginning, with a gentle introduction to Stata using the Graphical User Interface. The focus of this course is on learning how to use Stata to produce a clean, complete, analysis ready dataset. Along the way we will learn how to load data into Stata from different formats, familiarize ourselves with our data, correct errors, combine datasets, and generate new variables. Throughout the course we emphasise good research practice with the aim of enabling you to produce reliable and reproducible results. The course is applied and hands-on, with students following along from-the-front demonstrations and with plenty of opportunities for questions. The course will be delivered in eight 1.5 hour sessions over the two days. A comprehensive set of course notes will be given to all participants along with data used during the course and a set of example do-files.

Day 1

Session 1: Introduction to Stata

We start with a brief introduction to the course content and aims and to the Stata interface. We begin to learn how to use Stata through the Graphical User Interface (GUI). The GUI is a user-friendly way of working in Stata using drop-down menus and dialog boxes. As we work through a series of exercises we review the command syntax and begin to learn the structure of Stata commands. We also cover interpreting error messages and how to use Stata’s help facilities. At the end of the session we learn how to save commands that have been submitted so that they can be reused late.

Session 2: Getting to know your data

One of the most important stages of any statistical analysis is that of getting to know your data. We cover a number of key commands for exploring datasets and for summarizing variables of different types. We particularly focus on understanding what a dataset contains, the distributions of variables and identifying potential errors – which we will then see how to correct in later sessions.

Session 3: Creating and combining Stata datasets

In this session we learn how to import data from an Excel file into Stata and how to then save that data as a Stata dataset. Often in a research project you will be required to combine data from different files into a single dataset for analysis – we introduce two key commands for carrying out such a task. The goal here is to produce a single analysis dataset.

Session 4: Housekeeping

Housekeeping is the process of creating and maintaining a tidy, user-friendly dataset. Taking time to do this pays dividends later when you come to the analysis. We cover labelling variables, labelling the values of a variable, dropping unwanted variables and naming of variables.

Day 2

Session 5: Correcting and creating variables

This is another key stage in any statistical analysis. We will introduce commands for creating new variables (sometimes called derived variables) and for correcting errors and modifying existing variables. In this session we will focus on commands for dealing with numeric variables.

Session 6: String variables and dates

In this session we will cover some of Stata’s commands and functions for dealing with string variables, i.e. variables that consist of non-numeric values. We will also spend some time dealing with dates and learning how to covert a date that is in human readable form into a date that Stata can use.

Session 7: Collapsing and reshaping datasets

In this final taught session we will cover the creation of summary datasets (often useful when needing to produce a graph) and reshaping of datasets.

Session 8: Practical exercise

The final session consists of a data management challenge designed to help reinforce what has been taught over the previous seven sessions. The challenge will require importing and combining a number of Excel worksheets, checking and creating some new variables and producing a clean dataset ready for analysis.

Course 2: Data Visualisation through Stata (1-day)

12 December 2018

Course Overview

This one-day course assumes no prior experience with Stata, though some experience would be helpful. The focus of this course is on learning how to use Stata efficiently to visualise data effectively in figures and tables. The course is applied and hands-on, with students following along from-the-front demonstrations. There will be a comprehensive set of course notes to take away, along with data from the course and example do-files.

Session 1: Creating graphs through the graphical interface

In this first session we work interactively, creating graphs using the Graphical User Interface (GUI). We will start simply and gradually build a graph adding in options to create a publication ready figure. We cover box-and-whisker plots and also Stata’s twoway family of graphs which allow overlaying of plots to produce complex figures. Once we are happy with the graph we will learn how to take the command generated through the GUI and save it in a do-file ready for later use.

Session 2: Working efficiently in do-files

In this session we focus on building graph commands within do-files. We will learn how to lay out a long command in a do-file and how to then reproduce the graph. Being able to do this helps you to work much more efficiently – graphs can easily be reproduced, edited, and old graph commands can be recycled to produce new figures. We will learn a number of key options for improving the look of a graph and will also briefly visit Stata’s built Graph Editor which allows interactive editing of a Stata graph. We will also cover exporting graphs from Stata into a number of different formats including producing high resolution images.

Session 3: Visualising data in tables

In this session we move from figures to tables. We cover one-way and two-way frequency tables, as well as tables of summary statistics. This will be demonstrated using the GUI and through the command syntax working in a do-file. We will cover saving results in logfiles and copying tables from Stata into Word and Excel and show some tips for producing clear tables. There is a brief introduction to exporting results directly to Excel using the putexcel command.

Session 4: Practical Exercises

In this final supervised session there will be a number of graph or table challenges that will help reinforce what has been covered in the first three sessions. Students usually pick one or two of the challenges to work on through the session.

Course 3: Analysing Panel Data in Stata (2-days)

13 & 14 December 2018

Introduction to Panel Data

Session 1:

  • Brief summary of Stata’s main commands
  • Introduction to time series operators in Stata
  • Working with panel data in Stata
  • Summary of basic regression analysis

Session 2:

  • Regression and causality
  • Differences-in-Differences

Session 3:

  • Static panel data models
  • Fixed effects regressions
  • Random effects regressions

Session 4:

  • Practical session

Dynamic Panel Data Models

Session 5:

  • Dynamic panel data models
  • Challenges of dynamic panel data models

Session 6:

  • Instrumental-variable estimators
  • Generalised method of moment

Session 7:

  • The Arellano-Bond estimator
  • The Arellano–Bover/Blundell–Bond estimator
  • Misspecification Tests

Session 8:

  • Practical session

Course 4: Visualising Regression Models using Stata (1-day)

15 December 2018

This course is aimed for researchers from any field, with a basic knowledge of Stata, who are interested in present results effectively from any regression model-fitting using Stata commands designed for this purpose. 


Researchers from any field start to squirm when asked to give a simple explanation of the practical meaning of a non-linear relationship and/or an interaction from any type of regression model. Michael Mitchell’s book titled ‘Interpreting and Visualizing Regression Models Using Stata’ presented techniques that make answering those questions easy. This one-day course is mainly based in Mitchell’s book to introduce the way to present results from any model-fitting in a wide variety of settings in practice using the Stata commands margins and marginsplot 

Course Outline:

  • Type of regression models
  • Predictive margins, marginal effects and elasticity
  • Continuous and categorical predictors
  • Linear and non-linear relationships
  • 2-way and 3-way interactions
  • Practical exercises using the commands margins and marginsplot

Learning Ratio

Principal texts for pre/post course reading:

  • A Gentle Introduction to Stata, 4th Edition, Alan Acock (Stata Press)
  • Microeconometrics using Stata, Revised Edition, Colin Cameron and Pravin Trivedi (Stata Press)
  • A Visual Guide to Stata Graphics, 3rd Edition,
  • Introductory Econometrics: A Modern Approach, 5th Edition, Jeffrey Wooldridge (South-Western Cengage Learning)
  • Econometric Analysis of Panel Data, 5th Edition, Badi Baltagi (Wiley)
  • Interpreting and Visualizing Regression Models Using Stata (Stata Press)


Course 1: An Introduction to Stata and Data Management
No prior knowledge of Stata required. Knowledge of using other statistical software is an advantage but not necessary. 

Course 2: Data Visualisation through Stata 
Prior knowledge of Stata is not essential but very helpful; more specifically having familiarity with Stata’s interface and understanding of its syntax.

Course 3: Analysing Panel Data in Stata 
A basic understanding of Stata and familiarity with regression analysis are required. 

Course 4: Visualising Regression Models using Stata
Basic knowledge of Stata and regression models

More Information

Start Date

End Date


Summer schools

Study Options

Full Time


Regular fees: 480 - 1620 GBP

International Fees : 180 - 810 GBP

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Cost includes course materials, lunch and refreshments.
  • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. (Alternatively, laptops can be hired for a fee of £10.00 (ex. VAT) per day).
  • If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.
    • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of delegates is restricted. Please register early to guarantee your place.

Cass business School

London , United Kingdom

Start Date:

End Date:


United Kingdom



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