Centre for Applied Statistics Courses

We provide short courses in research methods and statistical analyses for anyone wanting to interpret or undertake their own research. Everyone is welcome to attend, including those based outside UCL.

Extensive notes are provided for all courses, and teaching is interspersed with practical examples and activities throughout courses to ensure that everyone has understood the key principles. We strive to create a relatively informal learning atmosphere, where participants are not afraid to ask questions or voice any confusion.

No prior statistical knowledge is assumed for our introductory course (Introduction to Research Methods and Statistics), or our summer schools, but all other courses assume that the basics are understood. Our courses usually take place on weekdays during typical office-hours and selected evening dates may also be available for certain courses depending on timetable availability.

The courses running frequently at CASC are:

Winter schools:

• Hybrid Winter school: Introduction to Statistics with R (12-16 February 2024)

Summer schools:

• Hybrid Summer school: Introduction to Statistics with R (New date to be confirmed)

Theory-based courses:

• Introduction to Research Methods and Statistics ✝§
• Critical Appraisal §
• Introduction to Logistic Regression *^§
• Introduction to Poisson Regression *^
• Introduction to Survival/Time-to-Event Data Analysis *^
• Assessing Measurement Reliability and Validity *
• Introduction to Bayesian Analysis *§
• Chi-square and Beyond for 2x2 Tables *
• Introduction to Latent Class Analysis *

Theory-based courses (with an optional software workshop):

• Introduction to Meta-Analysis *§ (with optional R workshop~)
• Introduction to Dealing with Missing Data *§ (with optional R/SPSS/Stata workshop)
• Introduction to Regression Analysis *§ (with optional SPSS/R/Stata workshop)

Mixed courses with integrated statistical theory and software:

• Sample Size Estimation and Power Calculations with Excel *✝
• Overview of Regressions with R *~^
• ANOVA/GLMs with SPSS *

Statistics software courses:

• Introduction to SPSS *✝
• Introduction to R *✝§
• Further Topics in R *~ 
• Introduction to Stata *✝
• Introduction to Data Analysis using MATLAB

Alternatively, please see the events calendar for a chronological list of statistics courses running at ICH (note: this calendar only shows the most imminent date for each course).

^{* Knowledge of basic statistical concepts is required/beneficial; we recommend the Introduction to Research Methods and Statistics course if you have little/no previous statistics experience; this course offers a good basis for all other CASC courses. 
~ requires prior knowledge/experience of the R software. 
^ We recommend attending the Introduction to Regression Analysis course first if you have no prior experience of regression analyses.} 
✝ ^{Evening dates often available for this course}
§ ^{Self-paced online materials available for purchase}