Introduction
Data Handling and Statistics 2 is the second of three applied statistics units offered by the School of Natural Sciences (Mathematics). This unit is designed to extend students' knowledge of statistical data analysis. It builds on the concepts introduced in Data Handling & Statistics 1 and gives a detailed treatment of regression and ANOVA within a general linear modelling framework. Students will become proficient in the use of a contemporary statistical package R, the interpretation of its output and reporting of statistical analyses to statisticians and to the general public. Students will be able to evaluate the appropriateness of experimental designs and statistical methods and suggest changes to designs and analyses.
Summary
| Unit name | Data Handling and Statistics 2 |
| Unit code | KMA253 |
| Credit points | 12.5 |
| College/School | Sciences and Engineering School of Natural Sciences |
| Discipline | Mathematics |
| Coordinator | Professor Barbara Holland |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
| Level | Intermediate |
Availability
Specific information on 2027 unit availability will be available in August
Learning Outcomes
- Understand and be able to explain both the need for and the limitations of statistical analyses applied to data from diverse sources including both observational studies and experimental designs.
- Apply theoretical and practical knowledge of modern statistical analysis to construct statistical models for a wide range of problems in various disciplines. Implement and test these models in the statistical software R.
- Interpret results of the statistical analyses and communicate the design of the experiment, the goal of the experiment and the analytical results to both statisticians and non-statisticians.
Fee Information
2027 fee information will be available in August.
Requisites
Prerequisites
(KMA153 - Data Handling and Statistics 1 OR KMA154 - Mathematics 1B)Teaching
| Teaching Pattern | 1 x 1-hour short pre-recorded videos, 1 x 1-hour live lecture (online), 1 x 2-hour computer lab (1 x 1-hour for distance offering with 1 hour independent prework expected), 1 x 1-hour optional Q&A session, ~4 hours self directed study (e.g. reading, working on assessment). |
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| Assessment | Project 1 (15%)|Project 2 (15%)|Project 3 (15%)|Online quizzes (20%)|Test (35%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
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The University reserves the right to amend or remove courses and unit availabilities, as appropriate.