1. ICIS Module Spec - BI1H57 Experimental Design and Data Manipulation
Saved on: Thursday 06 November 2014 08:48PM
BI1H57 - Experimental Design and Data Manipulation 09 MAY 2012 - 30 SEP 2018 |
Version 1
Associated Module Information
Module Code: BI1H57
Module Title: Experimental Design and Data Manipulation
Faculty: Faculty of Health, Sport and Science
Faculty Group: Department of Biology
Faculty Sub Group: N/A
Module Leader: David Lee
Module Team: Stuart I Hogg , John L Morton , Martin B Powell , Denis J Murphy , Clare
McVeigh , Tim P Johnson
First Intended Intake: NOV 2012 Final Year of Intake: NOV 2012
Date Validated: 27 NOV 2012 Date Closed: N/A
Credit Value: 10 Credit Level: 4 (Certificate (C))
Language: English
Percentage of Module Taught
0
in Welsh:
Equivalent Module: N/A
JACS Code:
ASC Code:
Document Version Information
Version: 1
Valid From: 09 MAY 2012
Valid To: 30 SEP 2018
Module Aims
To gain an understanding of hypothesis testing through appropriate experimental design and statistical analysis
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2. ICIS Module Spec - BI1H57 Experimental Design and Data Manipulation
Content Summary
Scientific method – originality. Hypothesis testing.
Experimental Design. Designing experiments with statistics in mind - discrimination, Replication and generality,
Controls.
'Blind' Designs Measurement (accuracy and precision).
Oral presentation skills
Scientific writing (research proposals, critical reviews, research papers)
Introduction to using Microsoft excel for graphics (scatter plots, line plots, bar charts, histograms
Introduction to statistics using Microsoft Excel and SPSS.
Introduction to Statistics
i) Common statistical terms
35
ii) Descriptive statistics: standard deviation, standard error, confidence intervals of mean.
iii) Deciding on what test to use.
iv) Non parametric vs parametrics.
Statistical tests to be selected from the following:
i) Student's t-test for comparing the means of two samples
ii) Paired-samples test.
iii) Analysis of variance for comparing means of three or more samples:
iv) For comparing separate treatments (One-way ANOVA)
v) Calculating the Least Significant Difference between means
vi) Using a Multiple Range Test for comparing means
vii) For factorial combinations of treatments (Two-way ANOVA)
viii) Chi-squared test for categories of data
ix) Poisson distribution for count data
x) Correlation coefficient and regression analysis for line fitting:
xi) Linear regression
xii) Logarithmic – dealing with the question scaling (allometry)
Learning and Teaching Methods
Activity Type Hours
Tutorial 24
Independent Study 76
Total Hours Selected 100
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3. ICIS Module Spec - BI1H57 Experimental Design and Data Manipulation
Learning Outcomes
# Learning Outcome
1 Understand the concept of hypothesis testing.
2 Be able to design an experiment in an appropriate manner to allow hypothesis testing through statistical
analysis.
3 Be able to write a full scientific paper using the correct format
4 Present a talk on a topic relevant to the student’s degree programme and critically review those of others.
5 Use common statistical methodologies employed in biosciences
6 Present data graphically using Microsoft Excel
Module Requisites
Pre / Co Requisites
Not Yet Completed
Other Requisites
Other Prerequisite(s):
N/A
Other Corequisite(s):
N/A
Assessment Criteria
Assessment
Assessment Description Duration Word
Weight
Category
Count
(%)
Best
of?
Oral
Assessment
Presentation 1 N/A N/A N/A 10 No
Set Exercise -
Time
Constrained
Classroom test - Time
constrained 1
statistic
exams
45 N/A 70 No
Written
Assignment
Research
plan/proposal/project/log
1
Research
proposal
N/A 500 10 No
Written
Assignment
Research
plan/proposal/project/log
2
Research
paper
N/A 500 10 No
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4. ICIS Module Spec - BI1H57 Experimental Design and Data Manipulation
Assessment Matrix
Learning Outcomes
Assessment Criteria 1 2 3 4 5 6
Classroom test - Time constrained 1 - - - - Yes Yes
Research plan/proposal/project/log 1 Yes Yes - - - -
Research plan/proposal/project/log 2 - - Yes - - -
Presentation 1 - - - Yes - -
Reading List
# Reading List Entry
1 Dytham C. (2010). Choosing and Using Statistics: A Biologist's Guide. 3rd Ed. Wiley-Blackwell.
2 Field A & Hole GJ (2002) How to Design and Report Experiments (Sage)
Key Skills
# Key Skill
1 1. Intellectual skills
2 2. Communication skills
3 3. Organisational skills
4 4. Interpersonal/teamwork skills
5 5. Research skills
6 6. Numeracy Skills
7 7. Computing and IT skills
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