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ST104 Statistical Laboratory 1

Throughout the 2020-21 academic year, we will be adapting the way we teach and assess your modules in line with government guidance on social distancing and other protective measures in response to Coronavirus. Teaching will vary between online and on-campus delivery through the year, and you should read the additional information linked on the right hand side of this page for details of how this will work for this module. The contact hours shown in the module information below are superseded by the additional information.You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus.

ST104-12 Statistical Laboratory I

Academic year
20/21
Department
Statistics
Level
Undergraduate Level 1
Module leader
Samuel Touchard
Credit value
12
Module duration
10 weeks
Assessment
Multiple
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.

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 simulate 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 Optional
Lectures 29 sessions of 1 hour (24%) 2 sessions of 1 hour
Practical classes 8 sessions of 1 hour (7%)
Private study 45 hours (38%)
Assessment 38 hours (32%)
Total 120 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 D2
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. 500 words is equivalent to one page of text, diagrams, formula or equations; your ST104 Laboratory Report 1 should not exceed 18 pages in length.

Laboratory Report 2 15% 18 hours

Due in Term 3 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. 500 words is equivalent to one page of text, diagrams, formula or equations; your ST104 Laboratory Report 2 should not exceed 18 pages in length.

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.

~Platforms - Moodle

Assessment group R
Weighting Study time
2 hour examination (September) 100%

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

~Platforms - Moodle

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

Courses

This module is Core for:

  • Year 1 of USTA-G302 Undergraduate Data Science
  • Year 1 of USTA-G304 Undergraduate Data Science (MSci)
  • Year 1 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
  • Year 1 of USTA-G1G3 Undergraduate Mathematics and Statistics (BSc MMathStat)
  • Year 1 of USTA-GG14 Undergraduate Mathematics and Statistics (BSc)
  • Year 1 of USTA-Y602 Undergraduate Mathematics,Operational Research,Statistics and Economics

This module is Option list B for:

  • Year 1 of UMAA-G100 Undergraduate Mathematics (BSc)
  • Year 1 of UMAA-G103 Undergraduate Mathematics (MMath)
  • Year 1 of UMAA-G106 Undergraduate Mathematics (MMath) with Study in Europe
  • Year 1 of UMAA-G1NC Undergraduate Mathematics and Business Studies
  • Year 1 of UMAA-G1N2 Undergraduate Mathematics and Business Studies (with Intercalated Year)
  • Year 1 of UMAA-GL11 Undergraduate Mathematics and Economics
  • Year 1 of UECA-GL12 Undergraduate Mathematics and Economics (with Intercalated Year)
  • Year 1 of UMAA-GV17 Undergraduate Mathematics and Philosophy
  • Year 1 of UMAA-GV18 Undergraduate Mathematics and Philosophy with Intercalated Year
  • Year 1 of UMAA-G101 Undergraduate Mathematics with Intercalated Year