A synopsis of the curriculum
• Descriptive statistics
• Contingency tables, Chi-squared test, Fisher's exact test
• T-tests
• Analysis of variance
• Correlation and regression
• Repeated measures
• Factorial and response surface designs
Blended distance learning:
Contact Hours: 100 hours
Private Study Time: 50 hours
Total Learning Time: 150 hours
Portfolio, two coursework assignments and exam
Weighting:
Essay Assignment 20%
Portfolio 20% - composed of 5 individual assignments where topics are applied to the workplace
2 hr Exam 60%
The pass mark for each individual assessment is 40%. All assessments must be passed in order to pass the module.
Spiegel, Murray (2014) Statistics. New York : McGraw-Hill Education.
Black, Beth (2012) A to Z of critical thinking. Continuum.
D. Holmes, P. Moody and D. Dine (2010) Research Methods for the Biosciences. Oxford University Press.
See the library reading list for this module (Medway)
The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
Show judgement in the selection and application of descriptive statistics.
Show judgement in the selection and application of contingency tables and the application of chi square and fisher exact tests Chi-squared and Fisher's exact tests.
Understand the proper use of controls and what is meant by 'control' group or condition.
Demonstrate systematic understanding of key aspects of random selection and assignment in experimental design.
Show judgement in the selection and application of parametric statistical tests such as t-tests and analysis of variance.
Understand the difference between categorical and continuous variables and the various statistical methods that can be applied to these variables.
Demonstrate systematic understanding of key aspects of correlation, simple linear and regression and multiple regression analysis statistics.
Understand what is meant by within-subjects factors and between-subject factors and what repeated measures are and when to apply a repeated measures ANOVA.
Understand factorial and response surface designs and how they can be applied to pharmacology.
The intended generic learning outcomes.
On successfully completing the module students will be able to:
Develop and demonstrate an ability to analyse, evaluate and correctly interpret data.
Present and communicate data effectively and confidently.
Obtain and use information from a variety of sources as part of self-directed learning.
Manage their time and use their organisation skills within the context of self-directed learning.
Develop and demonstrate an ability to work and communicate effectively with others.
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