Introduction to STATA - 22nd January 2014
The course provides an introductory training in STATA, a statistical package increasingly used for social research data analysis which has powerful data manipulation procedures and extensive and powerful statistical capabilities.

Introduction to Bayesian Analysis using WinBUGS - 23rd - 24th January 2014
Use of Bayesian methods is becoming increasingly widespread within quantitative social and health sciences, particularly for analysing data with complex structure, such as hierarchical or multilevel data. However, very few applied researchers have any formal training in Bayesian methods. This two-day course aims to introduce quantitative researchers to the basic principles of Bayesian inference and simulation-based methods for estimating Bayesian models, and to highlight some of the potential benefits that a Bayesian approach can offer. There is a large practical component to this course with time for hands-on data analysis using examples drawn mainly from the social and health sciences. No previous experience of Bayesian methods or WinBUGS is necessary.

Introduction to R - 5th February 2014
This course is aimed at people who wish to familiarise themselves with the freely available statistical analysis software R. R is a command language that can be used to carry out standard statistical analyses but also has powerful facilities to enable users to create their own routines or implement methods designed by other researchers. The course will: introduce participants to the R environment; explain how to enter data and run simple descriptive statistical methods; describe how to run standard procedures; show how to run commands designed by other researchers and how to develop commands for non-standard analyses. For background materials, software and reading please go to http://www.r-project.org/

Latent Factor Analysis - 7th February 2014
This short course covers latent variables and factor analysis at an introductory and intermediate level.  A latent variable is a thing (such as an attitude, an orientation, an experience or a level, e.g. the level of well-being) that has been measured using a set of related indicators.  A set of three or more indicators can be considered the manifest variables, from which a single latent variable might be derived.  Factor analysis is one way to derive a single factor from a set of variables, and is thus called a data reduction method. The course is suitable both for primary-data collection researchers (who may need to write a suitable questionnaire), and for those who want to analyse secondary data sets.

Cognitive Interviewing for Testing Survey Questions - 25th February 2014
This one day course is designed to familiarise participants with this powerful and efficient method of piloting survey questions called Cognitive Interviewing. This is a type of in-depth interviewing which focuses on respondents' thought processing in answering survey questions and uses specialised techniques such as thinking aloud, probing, observation and paraphrasing. The course is about what cognitive interviewing is as well as how to do it. There are practical exercises as well as lecture time.

Understanding Statistics - 26th February 2014
This course is an opportunity for participants to ask the basic statistical questions they have always wanted to ask. It focuses on basic statistical concepts such as: the four levels of measurement, measures of central tendency (median, mean, and mode), measures of dispersion (percentiles, variance, standard deviation, and standard error), confidence intervals, hypothesis testing, design effects and the issue of causality. These skills allow participants to interpret and evaluate existing research findings within the remit of basic statistics. The course is composed of a combination of lectures and practicals. The course will provide participants with the expertise required to evaluate the meaning, robustness and generalisability of basic statistical research findings.

Introduction to Sampling - 27th February 2014
This course introduces participants to what survey sampling is, why it is important, and how it is implemented. The course focuses on the practical aspects as well as some of the mathematics. It is composed of a combination of lectures and practicals. Content includes: types of samples, how to construct a ‘sampling frame’, types of probability samples (e.g., simple random, systematic, stratified, multi-stage clustered, unequal probabilities of selection), what ‘sampling error’ is, the role of sampling error in confidence intervals, how to determine sample size and an introduction to the effects of different types of sample designs on confidence intervals.

Introduction to Structural Equation Modelling using Mplus - 12-14th March 2014
Structural Equation Models (SEM) amalgamate regression analysis, path analysis and factor analysis, allowing for more richly detailed statistical models to be specified and compared to data than by using these techniques individually. Historically, SEM models were confined to the analysis of continuous observed data, limiting their usefulness in applied social research, where many phenomena are inherently discrete or are measured only with coarse-grained instruments. Advances in recent years have made SEM methods for categorical data available to applied researchers. This course aims to train quantitative social scientists to use the Mplus programme in the application of structural equation modelling techniques to non-continuous observed data.

Introduction to Data Analysis 1 - 20^th March 2014. This course provides an introduction to the theory and methods of quantitative data analysis, focussing on the social survey, with a focus on the use of crosstabulation to explore the relationship between categorical variables. It includes a series of practical sessions including using the statistical software package SPSS to explore a government dataset.

Introduction to Data Analysis 2 - 21st March 2014. This course provides an introduction to the theory and methods of quantitative data analysis for interval variables, focussing on the techniques of correlation and linear regression. It includes a series of practical sessions including using the statistical software package SPSS to explore a government survey dataset.

Statistics for Small Samples - 2nd April 2014. The course aims to cover bivariate statistical tests for a variety of situations. The basic material of t-test is enriched by adding methods for the comparison of the distribution (or a mean) in cases where the variable is not normally distributed The participants learn to critically assess the validity of claims to statistical inference (from sample to population) in small-N and medium-N situations. 

This course is delivered over two consecutive days and is aimed at those with no demographic training. The focus will be on the basic components of demographic change through measures and data sources to calculate and illustrate population structure, fertility, mortality and migration. Thus included are population pyramids, sex ratios, dependency ratios and fertility rates. The calculation of age-sex standardised ratios are also included in the course.

Multilevel Modelling - 14th May 2014
This one-day course begins with a description of some examples where multilevel models are useful in statistical analysis and some examples of multilevel populations. We then cover the basic theory of multilevel models and a brief introduction to software that has been written specifically for fitting multilevel models: MLwiN. No prior knowledge of multilevel modelling is assumed. Participants will get some experience of using MLwiN software.

Population Estimating and Forecasting - 14th May 2014
This course is aimed at those with a working knowledge of demography but having a need to expand this into the use of estimation and forecasting. The morning sessions will focus on relatively simple methods of estimating subnational populations. We then move onto more complex cohort-component methods. In the afternoon we learn how to forecast future populations and experiment with varying our assumptions about future demographic trends.
 
Demographic Forecasting with POPGROUP - 15th-16th May 2014
The course introduces the standard methods of forecasting population, households and the labour force, each with age and sex detail, through use of the POPGROUP software. Most time is spent on the more complex tasks of preparing population forecasts. The focus is on sub-national forecasts for districts of England and Wales, but the principles transfer directly to national forecasts, to sub-national forecasts of other areas, and to social or ethnic groups, each of which are discussed. The emphasis is on hands-on learning through practical sessions that take the participants through the preparation of inputs, running a forecast, analysing results, and adjusting forecasts to implement a range of scenarios or assumptions.

Longitudinal Data Analysis 21st-23rd May 2014
The importance of longitudinal analysis is becoming increasingly recognized across the social and medical sciences. The 3 days of intensive training will be made up of lectures and computer-lab examples and exercises implemented with appropriate statistical software. Participants will develop the skills needed to design longitudinal research and conduct  appropriate analyses using longitudinal data including the use of random effects models for repeated measures data and event history analysis.

Causal Modelling in Stata - 5th June 2014
Many analysts move from simple regression to more complex causal modelling. This course introduces basic techniques that are helpful for making statistical inferences in the intermediate level models: using a ‘long’ format panel data set; applying regression to panel data; drawing out causal interpretations. The course will also cover some causal concepts, describe statistical approaches to causal inference, give worked examples of regression models, and give hands-on experience in applied causal analysis using STATA.

There are a number of other courses available as part of the CCSR Short Course programme. For more information and to book please go to www.ccsr.ac.uk/courses/list 

New courses are likely to be added throughout the year.