Year
2020
Units
4.5
Contact
1 x 120-minute lecture weekly
1 x 50-minute workshop weekly
1 x 90-minute computer lab weekly
Prerequisites
1 STAT1121 - Data Science
1a STAT1122 - Biostatistics
1b STAT1412 - Data Analysis Laboratory
Must Satisfy: ((1 or 1a or 1b))
Enrolment not permitted
STAT2700 has been successfully completed
Topic description
Standard statistical analyses which are routinely encountered in applied science are introduced via case studies. The statistical principles and issues are discussed, and analyses are undertaken in the computer laboratory, without the need to examine underlying mathematical derivations or complex numerical formulae. This topic examines: data and data frames; exploratory data analysis; elements of statistical inference; simple experiments; strategies when assumptions fail; linear regression; linear regression with transformed variables; multiple regression; analysis of covariance; the one-way layout; the two-way layout; goodness of fit tests.
Educational aims
This topic aims to introduce students to standard statistical analyses which are routinely encountered in applied science. This aim will be achieved by involving the students directly in canonical problems in the computer laboratory
Expected learning outcomes
At the completion of this topic, students are expected to be able to:

  1. Identify the various techniques required
  2. Assess the validity of underlying assumptions
  3. Implement analyses using modern statistical computing software
  4. Present informed and critical summaries