Catalogue of Modules, University of Nottingham

A34636 Fundamentals in Statistics
(Last Updated:03 May 2017)

Year  17/18

Total Credits: 10

Level: Level 4

Target Students:  MSc/PGDip Sports and Exercise Medicine; MSc Applied Sport and Exercise Medicine There is a limited number of places on this module. Students are reminded that enrolments which are not agreed by the Offering School in advance may be cancelled without notice.

Taught Semesters:

SemesterAssessment
Spring Assessed by end of Designated Period 

Prerequisites: 

MnemTitle
A34621 Research Methods 

Corequisites:  None.

Summary of Content:  This module is aimed at providing the skills needed to enable a student to be able to quantitatively analyse their research data. It will cover how to undertake statistical analyses relevant to their research projects. This will be taught using a combination of tutorials, e-learning, formative assessments and computer practicals. Module Web Links:
   
  • Reading list
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  • Moodle
  • Method and Frequency of Class:

    ActivityNumber Of WeeksNumber of sessionsDuration of a session
    Lecture 1 weeks1 per week0 hours 30 mins
    Tutorial 5 weeks1 per week2 hours

    Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester

    Further Activity Details:

    20 minutes introductory lecture;
    5 x 2 hour tutorials with computer practical sessions;
    e-learning materials, to sit alongside the tutorials;
    1 formative assessment;
    self-study of the fundamentals of statistics - theory and practice, and use of statistical computer software: ~ 85 hours

    Method of Assessment: 

    Inclass Exam 1 (Practical) 100  Practical SPSS assessment - computer practical session (2 hours) 

    Convenor: 
    Dr R Pearson

    Education Aims:  The overall aim of this module is to enable students to have a good understanding of the fundamental principle behind basic and some more advanced statistics. This requires researchers to be able to formulate hypothesis to test the significance of differences in parametric and non-parametric data sets; this will initially focus on two variables using tests such as the t-test and Mann Whitney U test, then progress into analyses such as ANOVA and regression to enable multiple variables and confounders to be investigated. Data exploration and description will be covered which leads on to studying correlations. An example of the usefulness of specialised statistical methodology will be provided by survivorship analyses.

    Learning Outcomes:  Knowledge and understanding:

    Skills:

    Offering School:  Medicine


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