production
Skip to Content

PU5017: APPLIED STATISTICS (2017-2018)

Last modified: 13 Jul 2017 15:31


Course Overview

This course intends to develop the student's awareness of the fact that statistical techniques are integral to scientific research. Researchers must be able to specify a precise research question in statistical terms and then select an appropriate study design in order to carry out an effective research project. They must also be able to assess the adequacy of the research presented in scientific or medical literature. The same skills are also required for many MSc dissertation projects.



Course Details

Study Type Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Foresterhill Sustained Study No
Co-ordinators
  • Dr Gordon Prescott
  • Dr Shona Fielding

What courses & programmes must have been taken before this course?

  • One of PU5017 Applied Statistics (Studied) or MRes Drug Discovery (Studied) or MSc Clinical Pharmacology (Studied) or MSc Drug Discovery and Development (Studied) or MSc Human Nutrition (Studied) or MSc Global Health and Management (Studied) or MSc Public Health Research (Studied) or Master Of Public Health (Studied) or MSc Immunology (Studied) or MSc Health Psychology (Studied) or Master Of Science In Biotechnology, Bioinformatics And Bio-Business (Studied) or MSc Economics of Health (Studied) or MSc Bio-Business and Medical Sciences (Studied) or MSc Genetics (Studied) or MSc Microbiology (Studied)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

Are there a limited number of places available?

No

Course Description

What are data? Data types and presentation of data
What is chance? Probability
How does my data relate to the real world? Samples, distributions, statistical inference
Answering research questions with statistical techniques: Hypothesis testing
What if my data are awkward? Non-parametric methods
How does one variable relate to the other? Correlation and simple linear regression
How does one variable relate to several others? Multiple linear regression
Study design for research: Odds ratios and relative risks
Awkward data: Transformations
Relating binary health outcomes to other variables: Logistic regression

Further Information & Notes

This course is taken by students registered for a wide range of MSc programmes based in the School of Medicine, Medical Sciences and Nutrition and by some University staff. Everyone attending lectures must be registered for the course and complete all assessments.

This course equips the student with knowledge of statistical principles and statistical methods. In addition, the student will gain experience of analysing, presenting and interpreting numerical information.

Degree Programmes for which this Course is Prescribed

  • MRes Drug Discovery
  • MRes Medical Mycology and Fungal Immunology
  • MSc Clinical Pharmacology
  • MSc Drug Discovery and Development
  • MSc Genetics
  • MSc Global Health and Management
  • MSc Health Psychology
  • MSc Human Nutrition
  • MSc Immunology
  • MSc Microbiology
  • MSc Public Health Research
  • Master Of Public Health
  • Master Of Research In Medical Mycology For Clinicians
  • Master Of Science In Genetics And Human Nutrition

Contact Teaching Time

54 hours

This is the total time spent in lectures, tutorials and other class teaching.

Teaching Breakdown


Assessment

The course will be assessed using a multiple choice class test for 10%, a written assessment for 30% and an examination in January (60%).

Formative Assessment

None.

Feedback

None.

Compatibility Mode

We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.