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ST104 Statistical Laboratory 1

ST104-12 Statistical Laboratory I

Academic year
20/21
Department
Statistics
Level
Undergraduate Level 1
Module leader
Panayiota Constantinou
Credit value
12
Module duration
10 weeks
Assessment
30% coursework, 70% exam
Study location
University of Warwick main campus, Coventry
Introductory description

This module runs in the second half of term 2 and first half of term 3.

This module is core for students with their home department in Statistics and is also available for external students who have taken the necessary prerequisites. This module will be useful for ST221 Statistical Modelling and other modules which use statistical data analysis such as Programming for Data Science and Multivariate Statistics.

If you are an external student considering transferring to a course in Data Science, Mathematics and Statistics or MORSE you are encouraged to take ST104 Statistical Laboratory, but if you have not taken it, then the expectation is that you will learn independently how to program in R.

Pre-requisites:
Statistics Students: ST115 Introduction to Probability
Non-Statistics Students: ST111 Probability A and ST112 Probability B

Results from the coursework from this module may be partly used to determine of exemption eligibility in the computer based assessment components of the Institute and Faculty of Actuaries modules CS1, CS2, CM1 and CM2. (Independent application to the IFoA may be required.)

Module web page

Module aims

To introduce students to the R software package, making use of it for exploratory data analysis and simple simulations. This should deepen and reinforce the understanding of probabilistic notions being learnt in ST115 and ST111/2.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Introduction to R
Exploratory data analysis: methods of visualisation and summary statistics
Sampling from standard discrete and continuous distributions (Bernoulli, Geometric, Poisson, Gaussian, Gamma)
Generic methods for sampling from univariate distributions
The use of R to illustrate probabilistic notions such as conditioning, convolutions and the law of large numbers
Examples of modelling real data (but without formal statistical inference) and the use of visualisations to assess fit

Learning outcomes

By the end of the module, students should be able to:

  • Gain familiarity with the R software package, making use of it for exploratory data analysis.
  • Use R to stimulate samples from a variety of probability distributions.
  • Gain the ability to propose appropriate probabilistic models for simple data sets.
Indicative reading list

View reading list on Talis Aspire

Subject specific skills

TBC

Transferable skills

TBC

Study time

Type Required
Lectures 29 sessions of 1 hour (24%)
Practical classes 8 sessions of 1 hour (7%)
Private study 47 hours (39%)
Assessment 38 hours (31%)
Total 122 hours
Private study description

Weekly revision of lecture slides and materials, wider reading and practice exercises, developing familiarity with R programming language and preparing for examination.

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Students can register for this module without taking any assessment.

Assessment group D1
Weighting Study time
Laboratory Report 1 15% 18 hours

Due in Term 2 Week 10.
The first report will emphasise on R coding skills and/or other statistical questions.
The number of words noted below refers to the amount of time in hours that a well-prepared student who has attended lectures and carried out an appropriate amount of independent study on the material could expect to spend on this assignment.

Laboratory Report 2 15% 18 hours

Due in Term 2 Week 3.
The second report will emphasise on R as a simulation and visualisation tool and/or other statistical questions.
The number of words noted below refers to the amount of time in hours that a well-prepared student who has attended lectures and carried out an appropriate amount of independent study on the material could expect to spend on this assignment.

2 hour examination (Summer) 70% 2 hours

The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade.

Feedback on assessment

Reports will be marked and returned to students within 20 working days.

Solutions and cohort level feedback will be provided for the examination.

Past exam papers for ST104

There is currently no information about the courses for which this module is core or optional.