|Coordinator: Joanne Fearon
Dr Sean Lacey, CIT
***NOTE NEW DATES NOT YET CONFIRMED***
***COURSE FULL: APPLY FOR WAITING LIST PLACE***
This module is designed to provide an introduction to the design and application of statistical methods to research in the Agri-Food sector. No previous experience with statistical methods is assumed, Topics covered include: Descriptive Statistics, Statistical Graphics; Basic Probability concepts; Sampling and Sample Selection methods; Sampling Distributions; Estimation and Hypothesis Testing. Credits are available for and researcher who successfully completes an assigned project based on the material covered. NOTE: places are extremely limited on this course, you need to commit to all 3 days to be offered a place on the course.
PhD students with no, or limited, training in data analysis and statistics in Agri-Food Research.
|Learning outcomes and impact:|
On successful completion of this module, students should be able to:
Describe and summarise quantitative data;
Compute marginal, joint and conditional probabilities;
Describe and apply discrete and continuous distributions;
Recognise and identify the key elements of estimation and hypothesis testing;
Compute and interpret confidence intervals for a single mean and for the differences between two means;
Formulate hypotheses, interpret and derive conclusions from SPSS output for comparing means;
This module will be delivered via lectures and practical lab classes. Full attendance is required. SPSS will be used.
MCQ on final afternoon of module
The content of the course was extremely useful and interesting.
The lecturer has amazing speaking skills and it was very easy to follow him.
Good grounding in statistics from a very interesting teacher.
The information presented by the lecturer was clear and useful with many useful examples analysed in SPSS.
Basic concepts were explained very clearly.
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