• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
  • ANU College ANU College of Business and Economics
  • Classification Transitional
  • Course subject Statistics
  • Areas of interest Statistics
  • Academic career PGRD
  • Mode of delivery In Person
  • Co-taught Course

Statistics 3008/7001 (Applied Statistics) is a course designed for senior undergraduate and research students who need to design experiments and carry out statistical analysis of their data. Emphasis will be placed on the development of statistical concepts and statistical computing, rather than mathematical details. The content covered will be motivated by problem-solving in many diverse areas of application. The topics covered will include regression modelling with emphasis on model formulation, understanding the implication of model assumptions, diagnostic methods for model checking and interpretation, logistic regression for binary variables and binomial counts, log-linear regression for Poisson counts, and exploratory tools for summarising multivariate responses.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Demonstrate a deep understanding and usage of the statistical computing package R.
  2. Fit simple and multiple linear regression models and demonstrate model parameters.
  3. Explain in detail the relationships between a response variable and a covariate or covariates.
  4. Evaluate and Improve simple and multiple linear regression models based on - Perform diagnostic measures.
  5. Perform model selection in a multiple linear regression modelling context.
  6. Perform logistic and Poisson log-linear regression models.
  7. Demonstrate multivariate analyses techniques and the bootstrap.

Other Information

Indicative Assessment

  1. Typical assessment may include, but is not restricted to: assignments and a final exam. (null) [LO null]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.

Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course you must have completed STAT7055 or be enrolled in the Master of Statistics or MSc in Quantitative Biology and Bioinformatic or MSc in Quantitative Biology and Bioinformatic (Advanced). Incompatible with STAT3008.

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
1
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2023 $4320
International fee paying students
Year Fee
2023 $6180
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

There are no current offerings for this course.

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