°ÄÃÅÁùºÏ²Ê¿ª½±¼Ç¼
AP2A71-Experimental Design and Data Analysis
Module Provider: School of Agriculture, Policy and Development
Number of credits: 10 [5 ECTS credits]
Level:5
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2023/4
Module Convenor: Dr Alice Haughan
Email: a.haughan2@reading.ac.uk
Type of module:
Summary module description:
This module covers the principles of experimental design and common statistical methods for analysing datasets.
Aims:
To provide students with the ability to design experiments and to analyse and interpret the data.
Assessable learning outcomes:
Having completed this module students should be able to:
- Present data effectively in figures and tables suitable for reports and showing the variability in the data, for example using boxplots and similar, scatterplots
- Describe the concepts of:Ìýsummary statistics of location and spread; sources of chance variation; frequency distribution; confidence limit; significance; analysis of variance; correlation and regression; tests and measures o f association based on counts.
- Design an experiment with two factors and variation between units requiring blocking.
- Conduct analysis of variance, correlation test,Ìý regression analysis and chi squared test with standard software and interpret the results
- Report the method and results of a statistical analysis concisely whilst providing all key information.
Additional outcomes:
Critical approach to presentation and summary of data in all areas of life. Awareness of measures of uncertainty in science and their meaning. Greater numeracy. Improved confidence and selectivity with computer-based data-handling and analysis.
Outline content:
Critical understanding of experimental data is crucial to good decision-making in almost all parts of life. This module provides a working understanding of the logic of experimental design, practice in meaningful presentation of data, and the rationale of the most common statistical methods used in experiments in agricultural-related sciences.
Content includes: Data presentation methods and how they help (or otherwise) to clarify patterns and meaning; They key problem: dis tinguishing real effects from chance variation (i.e. signal from noise); Analysis of variance; Breaking complex questions into simpler ones; Principles of experimental design in the presence of background variation; Relationships between two (or more) measured characteristics;ÌýCritically examining patterns in count data (numbers of individuals in discrete groups).
Brief description of teaching and learning methods:
Problem/literature-driven explanations of concepts Multiple-choice tests designed to elicit and explain common misconceptions Practice in applying concepts using computer-based tools and widely used software Explanation and discussion of discipline-based published examples.
Ìý | Autumn | Spring | Summer |
Lectures | 10 | ||
Practicals classes and workshops | 20 | ||
Guided independent study: | Ìý | Ìý | Ìý |
Ìý Ìý Other | 50 | 10 | 10 |
Ìý | Ìý | Ìý | Ìý |
Total hours by term | 80 | 10 | 10 |
Ìý | Ìý | Ìý | Ìý |
Total hours for module | 100 |
Method | Percentage |
Set exercise | 50 |
Class test administered by School | 50 |
Summative assessment- Examinations:
Summative assessment- Coursework and in-class tests:
Set exercises based on practicals throughout the term
Computer-based Class test
Formative assessment methods:
In class mini-quizzes to check key concepts
Two formative set exercises based on practicals
Penalties for late submission:
The Support Centres will apply the following penalties for work submitted late:
- where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
- where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
A mark of 40% overallÌýbased on the criteria set out for undergraduate programmes.
Reassessment arrangements:
By coursework (computer-based test).
Additional Costs (specified where applicable):
1) Required text books:Ìý
2) Specialist equipment or materials:Ìý
3) Specialist clothing, footwear or headgear:Ìý
4) Printing and binding:Ìý
5) Computers and devices with a particular specification:Ìý
6) Travel, accommodation and subsistence:Ìý
Last updated: 23 November 2023
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.