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Analysis of Binary and Categorical Data

Overview
Many investigations often have data where there are only two, or a few, possible categories or response - for example a product may be accepted or rejected after inspection, a crop may or may not become infested with pests, a patient's symptoms can be classified as none, mild, moderate or severe.
This course will explain statistical techniques for studying associations between outcomes like those mentioned, and possible explanatory factors.  The emphasis will be on practical application and interpretation rather than theory.  A large compoenent of the course will be PC-based practical work on user-friendly statistics packages such as Minitab, R and Stata.

Who Should Attend?
Scientists and technologists who already have some statistical training but whose knowledge is lacking in the area of statistical methods specifically for binary and categorical data.  Prior attendance on A Review of Basic Statistics and Regression Analysis: A Hands-on Approach, or equivalent knowledge, is required for this course.

How You Will Benefit
You will be introduced to some of the necessary tools for summarising and analysing binary and categorical data, and learn how to fit and interpret models for exploring associations in such data.

What Do We Cover?
  • Graphical and tabular summaries of data
  • Chi-square tests of association between two categorical factors; validity, interpretation, limitations and residuals
  • Odds, and odds ratios
  • The concept of likelihood
  • Logistic models for binary and ordinal data

Available Software
This course has practical exercises written for: Minitab, R, Stata
Note: For practical work participants must bring their own laptop with a fully licensed version of the software they wish to use.


Course Dates
Next run to be announced

Duration: 2 days
Price: £TBC

Apply Now
(terms and conditions apply)

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  • Home
  • Training
    • Course Registration
    • Terms and Conditions
    • Bespoke Training
    • Mailing List Request
  • Consultancy
    • Expertise
  • Team
    • James Gallagher
    • Sandro Leidi
    • Dankmar Böhning
  • SSC-Stat
  • Resources
  • Contact us
  • Products