Fast. Accurate. Easy to use. Stata is a complete, integrated software package that provides all your data science needs—data manipulation, visualization, statistics, and automated reporting.
More about StataOur goal is to help delegates develop their existing skills and keep up-to-date with the latest and most important developments across the fields of Statistics, Econometrics and Forecasting.
View our coursesPresented by: Dr. Vincent O'Sullivan
This course is for professionals and researchers who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software. The participants will be introduced to Stata’s interface. They will be shown how manage and prepare datasets for analysis. The fundamentals of data analysis and visualization will also be taught.
More information14th - 19th June 2021.
Our Stata Summer school provides a very popular and flexible course framework allowing cost-effective attendance at any course separately, or the entire school. This is a great opportunity for students, academics and professionals to expand their econometrics skills and learn how they can apply econometrics and statistics from professionals pioneering research at the forefront of their specialist fields.
More informationDelivered by: Dr. Malvina Marchese, 7 May 2021
Struggling to write your dissertation with Stata? The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Stata to obtain any required econometrics.
More informationPresented by Dr. Giovanni Cerulli - 7 - 8 April 2021.
Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value from rows of large, and possibly noisy data. Click below to find out more.
More information29th April 2021, Presented by Dr. Malvina Marchese.
Our one hour online webinar provides a comprehensive introduction to Stata. It's an ideal course for beginners who want to get a head start, learning how to use Stata efficiently and effectively. Sign up below.
More information20th - 21st April, 2021.
This course will review the application of machine learning techniques to both prediction problems and so-called causal problems where a firm or policy maker needs to understand the impact of some form of intervention on a heterogeneous population.
More informationReview the proceedings from the London Stata Conference 2020: Download your slides here.
More informationIn this comprehensive study, Cerulli concentrates on 3 key areas: the pandemic's dynamic, predictions and statistical scenarios. You can watch the full interview here.
More informationUse Stata to easily import the latest official COVID-19 news from Johns Hopkins University
The command creates a table that contains the date, the number of confirmed cases, the number of deaths, and the number recovered, plus a calculated variable named 'newcases' - the difference between confirmed cases for two contiguous days.
More informationPresented By: Dr. Austin Nichols
This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.
Participants will be introduced to Stata and causal inference using practical examples. The fundamentals of data analysis and visualization will also be taught, using appropriate Stata commands and programming techniques
View full course detailsThis course is running online, via Zoom.
Mixed models have become increasingly popular, as they have many practical applications. However, the traditional linear mixed model with normally distributed errors may not always be appropriate for modelling discrete response variables, such as binary data and counts. Typically these types of responses are analysed using generalised linear models such as logistic regression and Poisson regression.
Commonly-used generalised linear models will be extended to deal with multiple error structures, using a variety of examples, generally drawn from medical and health related fields. Specific applications, such as repeated measurements and multi-centre trials will also be considered. For example, investigating the presence or absence of adverse events collected in a multi-centre clinical trial.
The emphasis will be on practical understanding, although an outline of the theory will be presented. Practical examples will be used to illustrate the methods, and participants will have the opportunity to fit and interpret models themselves in hands-on computer based practicals.
Note this course does not cover marginal or GEE type models, but will consider population-averaged effect measures derived from a generalised linear mixed model.
View full course detailsPresented by: Dr. Vincent O'Sullivan
This course is for professionals and researchers who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software. The participants will be introduced to Stata’s interface. They will be shown how manage and prepare datasets for analysis. The fundamentals of data analysis and visualization will also be taught. Then, the participants will be introduced to two of the main data analysis tools: linear regression and logistic regression. Participants will be taught the statistical theory behind these methods, and they will apply these methods to specially chosen datasets using examples from health research.
View full course detailsPresented by Dr. Giovanni Cerulli
This course will focus on three specific techniques: regression and classification trees (including bagging, random forests, and boosting), kernel-based regression, and global methods (step-wise, polynomial, spline, and series regressions).The teaching approach will be mainly based on the graphical language and intuition more so than on algebra. The training will make use of instructional as well as real-world examples, and will evenly balance theory and practical sessions.
The course is open to people coming from all scientific fields, but it is particularly targeted to researchers working in the medical, epidemiological and socio-economic sciences.
View full course detailsPresented by Dr. Giovanni Cerulli
This course provides participants with the essential tools, both theoretical and applied, for a proper use of instrumental variables (IV) and structural equation models (SEM) for statistical causal modelling using Stata.
View full course detailsThe aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Stata to obtain any required econometrics.
Participants will receive a free temporary Stata license for the duration of the course
The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of Stata is required.
View full course detailsPresented by Dr. Giovanni Cerulli
This course is a primer to machine learning techniques using Stata. Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value from rows of large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The training will make use of instructional as well as real-world examples, and will balance evenly theory and practical sessions.
View full course detailsPresented by Dr. Giovanni Cerulli
This course will focus on three specific techniques: regression and classification trees (including bagging, random forests, and boosting), kernel-based regression, and global methods (step-wise, polynomial, spline, and series regressions).The teaching approach will be mainly based on the graphical language and intuition more so than on algebra. The training will make use of instructional as well as real-world examples, and will evenly balance theory and practical sessions.
The course is open to people coming from all scientific fields, but it is particularly targeted to researchers working in the medical, epidemiological and socio-economic sciences.
View full course detailsPresented by Dr. Anis Samet
This workshop is an introduction to regression analysis with categorical dependent variables using the Stata software. It will cover the most commonly used regression models for categorical outcomes: binary logit and probit, ordinal logit, and multinomial logit.
The course assumes that attendees have prior knowledge of common commands in Stata to organize and handle data and undertake standard regression techniques. Nevertheless, this is an introductory course.
View full course details