• 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
• Course convener
• Dr Grace Chiu
• Tao Zou
• Mode of delivery In Person
• Offered in Autumn Session 2018
Second Semester 2018
Applied Statistics (STAT7001)

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:

Upon successful completion of the requirements for this course, students should have the knowledge and skills to:

• Demonstrate a deep understanding and usage of the statistical computing package R.

• Fit simple and multiple linear regression models and demonstrate model parameters.

• Explain in detail the relationships between a response variable and a covariate or covariates.

• Evaluate and Improve simple and multiple linear regression models based on • Perform diagnostic measures.

• Perform model selection in a multiple linear regression modelling context.

• Perform logistic and Poisson log-linear regression models.

• Demonstrate multivariate analyses techniques and the bootstrap.

## Other Information

See the course outline on the College courses page. Outlines are uploaded as they become available.

## Indicative Assessment

Typical assessment may include, but is not restricted to: assignments and a final exam.

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.

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.

## Requisite and Incompatibility

To enrol in this course you must have completed STAT7055 or be enrolled in the Master of Statistics, Master of Science in Quantitative Biology and Bioinformatic or advanced version. Incompatible with STAT6038

## Fees

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

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and 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). You can find your student contribution amount for each course 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

## Course fees

Domestic fee paying students
Year Fee
2018 \$3660
International fee paying students
Year Fee
2018 \$5160
Note: Please note that fee information is for current year only.

## Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

### Autumn Session

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
Intensive course
5794 28 May 2018 08 Jun 2018 08 Jun 2018 27 Jul 2018 In Person N/A

### Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
8495 23 Jul 2018 30 Jul 2018 31 Aug 2018 26 Oct 2018 In Person N/A