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  6. PU5017: Applied Statistics

PU5017: APPLIED STATISTICS (2021-2022)

Last modified: 31 May 2022 13:05


Course Overview

This course in Applied Statistics intends to focus on the application of statistical techniques in postgraduate research for health professionals, with a particular emphasis on the correct interpretation of statistical analyses. The course will NOT concentrate on the statistical theory underlying the subject. An important component of the course is the use of a statistical package, IBM SPSS Statistics 27, which can be used to implement all the methods taught on this course.

Course Details

Study Type Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Rute Vieira
  • Dr Mintu Nath

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

  • One of MRes Drug Discovery or MRes Medical Mycology and Fungal Immunology or MSc Clinical Pharmacology or MSc Drug Discovery and Development or MSc Human Nutrition or MSc Global Health and Management or Master Of Science In Health Data Science or MSc Public Health Research or Master Of Public Health or Master Of Science In Molecular Medicine or Master Of Research In Medical Mycology For Clinicians or MSc Immunology or Master Of Science In Immunology And Immunotherapy or MSc Health Psychology or Master Of Science In Biotechnology, Bioinformatics And Bio-Business or Master Of Science In Biotechnology And Bioinformatics or MSc Economics of Health or MSc Bio-Business and Medical Sciences or Master Of Research In Medical Sciences or Master Of Science In Reproductive And Developmental Biology or MSc Genetics or MSc Microbiology or Master Of Science In Industrial Biotechnology

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
  • Probability and probability distributions
  • How do my data relate to the real world? Sampling distributions, statistical inference and introduction to hypothesis testing
  • Hypothesis testing for continuous data: t-test
  • Hypothesis testing for continuous data: ANOVA
  • Hypothesis testing for continuous data: non-parametric tests
  • Hypothesis testing for categorical data
  • Relative risk, odds ratio and related terms. Correlation and measures of agreement
  • Simple Linear Regression
  • Multiple linear regression and logistic regression

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

Class Test - Multiple Choice Questions

Assessment Type Summative Weighting 10
Assessment Weeks 19 Feedback Weeks 20

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Feedback

Each question has feedback on wrong answers submitted and how to arrive at correct answer. Feedback received once grades released, a few days after the due date.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralApplyApply suitable statistical methods to answer research questions in a variety of contexts and study designs
ProceduralApplyApply the concept of statistical inference to health research
ReflectionAnalyseDemonstrate the ability to present and interpret results from statistical analyses appropriately

Class Test - Multiple Choice Questions

Assessment Type Summative Weighting 20
Assessment Weeks 16 Feedback Weeks 17

Look up Week Numbers

Feedback

Each question has feedback on wrong answers submitted and how to arrive at correct answer. Feedback received once grades released, a few days after the due date.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualEvaluateDemonstrate the ability to critically appraise the presentation and interpretation of results in the literature
ProceduralApplyApply suitable statistical methods to answer research questions in a variety of contexts and study designs
ProceduralApplyApply the concept of statistical inference to health research
ReflectionAnalyseDemonstrate the ability to present and interpret results from statistical analyses appropriately

Report: Individual

Assessment Type Summative Weighting 60
Assessment Weeks 18 Feedback Weeks 20

Look up Week Numbers

Feedback

The assessment is marked with a rubric covering different themes within the assessment, each theme is marked and the combined grade obtained.

The student will get one or two sentences of feedback from the marker per theme.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralApplyApply suitable statistical methods to answer research questions in a variety of contexts and study designs
ProceduralApplyApply the concept of statistical inference to health research
ProceduralApplyDevelop a working knowledge of a statistical software package for data management and analysis
ReflectionAnalyseDemonstrate the ability to present and interpret results from statistical analyses appropriately

Class Test - Multiple Choice Questions

Assessment Type Summative Weighting 10
Assessment Weeks 12 Feedback Weeks 13

Look up Week Numbers

Feedback

Each question has feedback on wrong answers submitted and how to arrive at correct answer. Feedback received once grades released, a few days after the due date.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralApplyApply the concept of statistical inference to health research
ReflectionAnalyseDemonstrate the ability to present and interpret results from statistical analyses appropriately

Formative Assessment

There are no assessments for this course.

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualEvaluateDemonstrate the ability to critically appraise the presentation and interpretation of results in the literature
ProceduralApplyApply the concept of statistical inference to health research
ReflectionAnalyseDemonstrate the ability to present and interpret results from statistical analyses appropriately
ProceduralApplyDevelop a working knowledge of a statistical software package for data management and analysis
ProceduralApplyApply suitable statistical methods to answer research questions in a variety of contexts and study designs
 

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