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.)
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.
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
By the end of the module, students should be able to:
View reading list on Talis Aspire
TBC
TBC
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 
Weekly revision of lecture slides and materials, wider reading and practice exercises, developing familiarity with R programming language and preparing for examination.
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.
Weighting  Study time  

Laboratory Report 1  15%  18 hours 
Due in Term 2 Week 10. 

Laboratory Report 2  15%  18 hours 
Due in Term 3 Week 3. 

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

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.

Reports will be marked and returned to students within 20 working days.
Solutions and cohort level feedback will be provided for the examination.
This module is Core for:
This module is Option list B for: