Data Handling and Statistics 2
UndergraduateTAS-KMA2532025
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- Study method
- 100% online
- Assessments
- 100% online
- Entry requirements
- Prior study needed
- Duration
- 14 weeks
- Start dates
- 21 July 2025
- Loan available
- HECS-HELP and FEE-HELP available
Data Handling and Statistics 2
About this subject
On successful completion of this subject, students will be able to:
- Understand and 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.
- Hypothesis Testing
- ANOVA
- Simple Linear Regression
- Coping when Regression Assumptions aren't met
- Multiple Regression
- Extending the Linear Model to Categorical Variables
- Influence and Diagnostics for Multiple Regression
- Experimental Design
- Design and Analysis of Experiments: Two case studies
- Tools for Tables of Counts
- Logistic Regression
- Log-Linear (Poisson) Regression
Data Handling and Statistics 2 is the second of three applied statistics subjects offered by the School of Natural Sciences (Mathematics). This subject 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.
- Test (35%)
- Online Quizzes (x 6) (20%)
- Project 1 (15%)
- Project 2 (15%)
- Project 3 (15%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
Prior study
You must have successfully completed the following subject(s) before starting this subject:
one of
Additional requirements
- Other requirements - Teaching Arrangement: 1 x 1-hour short pre-recorded videos, 1 x 1-hour live lecture (online), 1 x 1-hour online lab with 1 hour independent prework expected, 1 x 1-hour optional Q&A session, approximately 4 hours self directed study (e.g. reading, working on assessment) weekly.
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.
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