Module Details

Title: Statistics for Agri-Food Researchers - UCC
Coordinator: Joanne Fearon Contributors:

Dr Sean Lacey, CIT



UCC staff


Outline:

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.


Target audience:

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;


Module delivery:

This module will be delivered via lectures and practical lab classes. Full attendance is required. SPSS will be used.


Module assessment:

MCQ on final afternoon of module


Testimonial:

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.



Excellent handouts.



Basic concepts were explained very clearly.



 


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