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.
Prerequisites:
Statistics Students: ST115 Introduction to Probability
NonStatistics 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 (35%)

2 sessions of 1 hour

Practical classes 
8 sessions of 1 hour (10%)


Private study 
45 hours (55%)


Total 
82 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 wellprepared 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 wellprepared 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.

Inperson Examination

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
 Answerbook Pink (12 page)
 Students may use a calculator
 Graph paper
 Cambridge Statistical Tables (blue)

Assessment group R

Weighting 
Study time 
Inperson Examination  Resit

100%


The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade.
 Answerbook Pink (12 page)
 Students may use a calculator
 Graph paper
 Cambridge Statistical Tables (blue)

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:

USTAG302 Undergraduate Data Science

Year 1 of
G302 Data Science

Year 1 of
G302 Data Science

Year 1 of
USTAG304 Undergraduate Data Science (MSci)

Year 1 of
USTAG300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics

Year 1 of
USTAG1G3 Undergraduate Mathematics and Statistics (BSc MMathStat)

USTAGG14 Undergraduate Mathematics and Statistics (BSc)

Year 1 of
GG14 Mathematics and Statistics

Year 1 of
GG14 Mathematics and Statistics

USTAY602 Undergraduate Mathematics,Operational Research,Statistics and Economics

Year 1 of
Y602 Mathematics,Operational Research,Stats,Economics

Year 1 of
Y602 Mathematics,Operational Research,Stats,Economics
This module is Option list B for:

UMAAG100 Undergraduate Mathematics (BSc)

Year 1 of
G100 Mathematics

Year 1 of
G100 Mathematics

Year 1 of
G100 Mathematics

UMAAG103 Undergraduate Mathematics (MMath)

Year 1 of
G100 Mathematics

Year 1 of
G103 Mathematics (MMath)

Year 1 of
G103 Mathematics (MMath)

Year 1 of
UMAAG106 Undergraduate Mathematics (MMath) with Study in Europe

Year 1 of
UMAAG1NC Undergraduate Mathematics and Business Studies

Year 1 of
UMAAG1N2 Undergraduate Mathematics and Business Studies (with Intercalated Year)

Year 1 of
UMAAGL11 Undergraduate Mathematics and Economics

Year 1 of
UECAGL12 Undergraduate Mathematics and Economics (with Intercalated Year)

UMAAGV17 Undergraduate Mathematics and Philosophy

Year 1 of
GV17 Mathematics and Philosophy

Year 1 of
GV17 Mathematics and Philosophy

Year 1 of
GV17 Mathematics and Philosophy

UMAAGV18 Undergraduate Mathematics and Philosophy with Intercalated Year

Year 1 of
GV18 Mathematics and Philosophy with Intercalated Year

Year 1 of
GV18 Mathematics and Philosophy with Intercalated Year

Year 1 of
UMAAG101 Undergraduate Mathematics with Intercalated Year