The University of Southampton
Courses

# STAT6103 Statistical Programming

## Module Overview

This module aims to give students a grounding in the use of statistical software for data manipulation, analysis and simulation. It uses the R software as a basis, because of its wide functionality and close links with data science. Other software more suited to bulk processing will also be discussed.

### Aims and Objectives

#### Module Aims

The aims of the module are: To prepare students to input, verify, organise, modify, combine, analyse and present data using a range of computing and statistical methods implemented in the general purpose statistical package R . It also aims to introduce some basic ideas of statistical computing, such as numerical methods used to obtain summary statistics, iterative methods for solving equations, and simulation. Focus is not on detailed explanation of statistical analysis methods, but several of these methods will feature as examples during the module

#### Learning Outcomes

##### Learning Outcomes

Having successfully completed this module you will be able to:

• Enter and manipulate data within R.
• Perform standard statistical analyses using R and interpret the resulting output for a wide range of statistical data that arise in government.
• Obtain additional information on how to perform advanced statistical analyses using R and then undertake such analyses.
• Interface R with data science software to deal with different types of data.
• Work independently in retrieving, organising and analysing data from surveys, censuses, and administrative sources.

### Syllabus

Introduction to R. R basics. Data management in R. R functions for statistical analysis: linear regression and more. Advanced data management and SAS . Statistical computing in R. Simulation. Interfacing R with Python and other data processing/management software.

#### Special Features

Computer lab sessions are used to enable students to gain practical experience using the statistical software used in the course and carry out exercises designed to reinforce the ideas presented in the lectures. This module is run as a week-long short course, a component of the MSc Official Statistics.

### Learning and Teaching

#### Teaching and learning methods

A variety of methods will be used including lectures and workshops/tutorials, mixed in a 5 day course designed for students on release from the workplace. Students are also expected to read wider than the lecture material as part of their individual study, and to critically appraise different approaches.

TypeHours
Independent Study80
Teaching20
Total study time100

### Assessment

#### Summative

MethodPercentage contribution
Coursework  ( words) 100%

#### Referral

MethodPercentage contribution
Coursework 100%

#### Repeat Information

Repeat type: Internal & External