Essentials of Survey Research Design
|Royal Statistical Society|
Dr. Pamela Campanelli
22/06/2021 - 23/06/2021
View in Google Maps (EC1Y 8LX)
Surveys are a key component of quantitative research whether this is for government, academia, research institutes, or other organisations. The recent explosion of easy-to-use web survey packages means that everyone thinks they can do a survey. However, generating statistically unbiased and reliable data is more complex than writing a few questions. Without proper instruction, the conclusions drawn from a survey can be flawed and misleading. This course looks at each of the quality areas for producing a successful and efficient quantitative survey. It covers all the major methods of data collection (quantitative interviewing, web and paper self-completion) as well as all the key aspects of the survey process from initial design through implementation through post-field processing. It focuses on the practical details of conducting a survey as well as including crucial tips from what is known in the survey methodology and statistical literature.
Attendees with no experience in GAM modelling will get an understanding of what GAM models are, when are they useful and how can they be used to perform statistical analysis, for inferential or predictive purposes. Attendees who have some experience with GAMs will learn about the new Big Data and visual GAM methods, as well as about GAMLSS models and quantile GAMs.
The target audience are practictioners, either in industry or academia, interested in learning new powerful statistical methods, which can be used in a wide variety of applications such as rainfall modelling, electricity demand forecasting, survival analysis and air pollution modelling to name a few.
Attendees should have some background on (linear) regression modelling, and a good understanding of fundamental statistical concepts such as probability densities, quantiles, etc. Some basic proficiency with R (eg. loading data, accessing data frames, basic use of the lm() function), at a level equivalent to a couple of days of self-study, is also assumed.
Attendees will need to bring a laptop with a recent version of R installed. Prior to the course attendees will be asked to install some additional R packages.
Entry (no or almost no prior knowledge)
£588 - £816 (inc. VAT)
Website and registration
Quantitative Data Handling and Data Analysis
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