• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
  • ANU College ANU College of Business and Economics
  • Course subject Statistics
  • Areas of interest Actuarial Studies, Finance, Statistics
STAT2008/STAT/4038/STAT6038 is a course in applied statistics that studies the use of linear regression techniques for examining relationships between variables. The course emphasizes the principles of statistical modelling through the iterative process of fitting a model, examining the fit to assess imperfections in the model and suggest alternative models, and continuing until a satisfactory model is reached. Both steps in this process require the use of a computer: model fitting uses various numerical algorithms, and model assessment involves extensive use of graphical displays. The R statistical computing package is used as an integral part of the course.
 

Learning Outcomes

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

  1. Demonstrate a thorough understanding of the R statistical computing language, particularly the graphical capabilities.
  2. Fit simple linear regression models, interpret model parameters and relate theses back to the underlying research question.
  3. Analyse and interpret relatiosnhips between a response variable and a covariate.
  4. Analyse and interpret relationships between a response variable and several covariates.
  5. Assess and refine simple and multiple linear regression models based on diagnostic measures. Identify and discuss the implications of outlying and influential data points.
  6. Select and discuss a useful multiple linear regression model from a number of competing models.

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

Incompatible with STAT2008 and STAT2014.

You will need to contact the Rsch Sch of Finance, Actuarial Studies & App Stats to request a permission code to enrol in this course.

Prescribed Texts

None specified

Assumed Knowledge

It is assumed that students will have completed STAT1003 or STAT1008 before requesting permission to enrol in this course.

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
Domestic fee paying students
Year Fee
2019 $3840
International fee paying students
Year Fee
2019 $5460
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
4015 25 Feb 2019 04 Mar 2019 31 Mar 2019 31 May 2019 In Person View

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
9897 22 Jul 2019 29 Jul 2019 31 Aug 2019 25 Oct 2019 In Person View

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