Data Management and Analytics using SAS (Level M) STATS5066

  • Academic Session: 2018-19
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

This course provides an in-depth introduction to the statistical software package SAS, including the use of Structured Query Language (SQL). It covers all the features required for SAS certification as a Certified SAS Base Programmer and a Certified SAS Statistical Business Analyst

Timetable

15 two-hour labs

Requirements of Entry

A-Level Mathematics (at grade A or better), or equivalent

Excluded Courses

STATS4062 Data Management and Analytics using SAS

Assessment

85% Coursework (in-class tests and homework exercises)
15% Project

Are reassessment opportunities available for all summative assessments? Not applicable

Reassessments are normally available for all courses, except those which contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Course Aims

This course aims to provide students with experience of programming and data management using SAS, including running basic database queries with Structured Query Language (SQL). It also illustrates how SAS can be used to carry out a wide variety of statistical analyses

Intended Learning Outcomes of Course

By the end of this course students will be able :

■ Manipulate, transform and combine data sets in SAS

■ Import and export raw data files

■ Create basic detail and summary reports using SAS procedures

■ Identify and correct data, syntax and programming logic errors

■ Formulate basic queries in SQL

■ Fit standard statistical models using SAS procedures such as TTEST, REG, GLM, GLMTEST, LOGISTIC, GENMOD and SCORE, and assess their performance

Use their knowledge of SAS procedures to analyse a complex real-world data set and summarize the results in a report.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.