Courses for the 54th Essex Summer School in Social Science Data Analysis.

All courses are offered online.

For enquiries, please contact us at esumsda@essex.ac.uk
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Courses take place in Mornings or Afternoons, British Summer Time (BST).
The schedule for each session is described in the menu on the left.
Further information on online course delivery can be found here


****IMPORTANT NOTE: Applications for session one will close on 18 June 2021****

SESSION ONE: Sunday 11 July to Friday 23 July 2021

One-day course: Sunday 11th July
1X Introduction to R (6 hours)

Two-week courses (35 hours): 12 – 23 July
1A Mathematics 1 (15 hours) 
1B Introduction to Quantitative Text Analysis N.B. Course is now full. We continue to welcome applications but please be advised these will be added to a waiting list.
1C Introduction to Regression
1D Introduction to Social Network Analysis N.B. Course is now full. We continue to welcome applications but please be advised these will be added to a waiting list.
1E Introduction to Multilevel Models 
1F Introduction to Statistics for Survey Data Analysis 
1G Longitudinal Data Analysis
1H Qualitative Data Analysis: Methodologies for Analysing Text and Talk N.B. Course is now full. We continue to welcome applications but please be advised these will be added to a waiting list.
1I Qualitative Interviewing  N.B. Course is now full. We continue to welcome applications but please be advised these will be added to a waiting list.
1J Beyond OLS: Categorical, Choice and Count Models
1K Introduction to Programming in Python for Social Scientists
1L Web Scraping and Data Management for Social Scientists
1N Methods for Fieldwork in Social Science
1Q Doing Discourse Analysis: Populism, Neoliberalism and Radical Democratic Politics

One-week course, week 1 of session 1: 12 July – 16 July

1P Introduction to GIS, Geospatial Data and Spatial Analysis (17.5 hours)  N.B. Course is now full. We continue to welcome applications but please be advised these will be added to a waiting list.
1R Introduction to Longitudinal Data Research Using R: From Data Management to Reproducible Research (17.5 hours)

One-week courses (week 2 of session 1): 19 July – 23 July

1S Quantitative Methods for Surveying Hard to Reach Populations (17.5 hours) 

SESSION TWO: Sunday 25th July to Friday 6 August

One-day course, Sunday 25th

2X Introduction to R (6 hours)

Two-week courses (35 hours)  
2A Mathematics part 2 (15 hours)
2B Quantitative Data Analysis and Statistical Graphics with R
2C Advanced Survey Data Analysis and Survey Experiments
2D Case Study Methods
2E Multilevel Models: Practical Applications
2F Advanced Methods for Social Media & Textual Data
2G Panel Data Analysis for Comparative Research
2H Mixed Methods Research
2I Applying Discourse Theory – Politics, Ideology, Populism
2J Machine Learning for Social Scientists
2K Causal Inference and Experiments in the Social Sciences
2L Introduction to Quantitative Methods in R
2M Introduction to Applied Bayesian Statistics
2N Confirmatory Factor Analysis & Structural Equation Modelling
2P Advanced Methods for Text-as-Data: Natural Language Processing
2S Introduction to Statistics for Social Science Research with SPSS

One-week courses (week 1 of session 2)
2Q
Ethnography and Ethnographic Methods (35 hours) N.B. Course is now full. We continue to welcome applications but please be advised these will be added to a waiting list.
2R Advanced Social Network Analysis – Cross-sectional and Longitudinal Social Network Analysis (17.5 hours)

One-week courses (week 2 of session 2)
2T
Survival Analysis and Event History Modelling (17.5 hours)

SESSION THREE: Sunday 8 August to Friday 20 August

One-day course Sunday 8 August

3X Introduction to R (6 hours)

Two-week courses (35 hours)
3A Mathematics part 3 (15 hours)
3B Quantitative Text Analysis
3D Computational methods for Social Data Science: Exploring Society through Visualization and Modelling
3F Bayesian Analysis for the Social and Behavioural Sciences
3G Quantitative Methods for Causal Inference and Policy Evaluation
3H
Spatial Econometrics
3J Advanced Quantitative Methods
3K Time Series and Panel Models for Dynamic and Heterogeneous Processes
3L
Scaling Methods for Social Science: Measurement, IRT and Ideal Point Estimation for Surveys and Behavior
3N Advanced Machine Learning For Social Scientists

One-week course (week 1 of session 3): 9 – 13 August
3P
Agent-Based Models (17.5 hours)