AP2A61-Experimentation 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: 2018/9

Module Convenor: Dr Lindsay Todman

Email: l.todman@reading.ac.uk

Type of module:

Summary module description:

To provide students with the ability to design experiments and to analyse and interpret the data arising in contexts relevant to their specialisms

Aims:

To provide students with the ability to design experiments and to analyse and interpret the data arising in contexts relevant to their specialisms

Assessable learning outcomes:

Effective presentation of datasets typical of the student’s main area of study, to show location, spread or relationship as appropriate, correctly using whisker-plots and similar, scatterplots.  Sound description of concepts of:  summary statistics of location and spread; sources of chance variation; frequency distribution; confidence limit; significance; analysis of variance; correlation and regression; tests and measures of association based on counts.

Ability to design an experiment with two factors and variation between units requiring blocking. Ability to conduct analysis of variance, correlation and regression analysis with standard software and interpret the results in a context similar to the student’s main area of study. Spotting specific common errors in experimental design. Ability to write a report with appropriately constructed figures and tables with appropriate legends.

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: telling real effects from chance variation: 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. Critically 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 paper- or computer-based tools and widely used software Specific data-set simulations and computer-based experimental design tools Explanation and discussion of discipline-based published examples

Contact hours:

	Autumn	Spring	Summer
Lectures	20
Practicals classes and workshops	10
Guided independent study	50	10	10
Total hours by term	80.00	10.00	10.00
Total hours for module	100.00

Summative Assessment Methods:

Method	Percentage
Set exercise	40
Class test administered by School	60

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Formative assessment methods:

Computer-based tests and simulations

Feedback on summative assessment reports

Penalties for late submission:
The Module Convener 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[1] (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.

The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
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% overall based on the criteria set out for undergraduate programmes.

Reassessment arrangements:

By coursework (computer-based test).

Additional Costs (specified where applicable):
1) Required text books:
2) Specialist equipment or materials:
3) Specialist clothing, footwear or headgear:
4) Printing and binding:
5) Computers and devices with a particular specification:
6) Travel, accommodation and subsistence:

Last updated: 30 July 2018