The University of Southampton
Courses

# MATH6166 Statistical Computing for Data Scientists

## Module Overview

Introduction to the statistical packages R and SAS. The module will consist of two sets of lectures and associated computer workshops, one each in R and SAS.

### Aims and Objectives

#### Module Aims

The aims of the module are: To introduce a range of statistical methods implemented on computers; to give practice in applying methods and interpreting results from them; to develop the use of computers with particular emphasis on R and SAS in the collection, validation, analysis and presentation of data; to help develop the knowledge and experience necessary to implement statistical computing methods.

#### Learning Outcomes

##### Learning Outcomes

Having successfully completed this module you will be able to:

• enter and manipulate data within SAS and R
• perform basic statistical analyses using SAS and R and interpret the output
• find information on how to perform advanced statistical analyses using R, and then undertake such analyses.

### Syllabus

• Data manipulation in R and SAS • Using the Help menu • Writing functions in R • Conditional execution and loops in R • Graphics in R • Apply the above programming skills in R to problems arising in data analysis • Interpretation of R output • Important commands in SAS, and their syntax • Interpretation of SAS output

### Learning and Teaching

#### Teaching and learning methods

9 lectures (6 in R, 3 in SAS) and 9 computer labs (6 in R, 3 in SAS)

TypeHours
Completion of assessment task27
Follow-up work12
Wider reading or practice12
Practical classes and workshops6
Lecture6
Preparation for scheduled sessions12
Total study time75

#### Resources & Reading list

Der, G. and Everitt, B.S. (2006). Statistical Analysis of Medical data Using SAS.

Garrett Grolemund and Hadley Wickham. R for Data Science.

### Assessment

#### Assessment Strategy

Coursework - a combination of R and SAS coursework with 50% weighting each

#### Summative

MethodPercentage contribution
Coursework 100%

#### Referral

MethodPercentage contribution
Coursework 100%

#### Repeat Information

Repeat type: Internal & External

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