STAT4063 Computationally Intensive Methods in Statistics
- 6 points
If this unit does not have an online alternative, then students who are presently unable to enter Western Australia and whose studies would be delayed by an inability to complete this unit, should contact the unit coordinator (details given on this page) to ascertain, on an individual case-by-case basis, if alternate arrangements can be made to support their study in this unit.
Availability Location Mode Semester 2 UWA (Perth) Face to face Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
- Details for undergraduate courses
- Level 4 elective
- Honours option in Mathematics and Statistics [Bachelor of Science (Honours)]
- The explosion in power of computers over recent times is changing the face of statistical science. Once upon a time, intuitively attractive statistical procedures had to be consigned to the waste bin if they led to unfathomable mathematical complications, or required masses of intricate calculations for their practical implementation. Now such difficulties can often be circumvented by using computer simulation and number crunching. This has led to the development and widespread use of many new statistical tools including the bootstrap, Markov Chain Monte Carlo methods and non-parametric kernel smoothing methods. Computer intensive statistical methods are not only in general use by statisticians, but are also applied by quantitative researchers in the life sciences, medicine and biological science, social sciences and business.
This unit gives a broad coverage of computer intensive methods with numerous applied examples, together with the underlying general concepts and basic theory. Particular emphasis is placed on the use of these methods in real statistical applications. Data sets are analysed using the statistical package R. Topics are selected from the following: simulation and Monte Carlo, bootstrap methods, Markov Chain Monte Carlo (MCMC) methods and Bayesian inference, non-parametric kernel smoothing methods, and statistical/machine learning.
- Students are able to (1) appropriately apply computationally intensive statistical techniques in simulation studies and to real-world problems; (2) extend their knowledge of computational techniques in general, but statistical computing techniques in particular, and adapt known solutions to different situations; and (3) present results in a logical and coherent fashion and communicate effectively with others.
- Indicative assessments in this unit are as follows: (1) assignments and (2) a final examination. Further information is available in the unit outline.
Supplementary assessment is not available in this unit.
- Unit Coordinator(s)
- Dr Edward Cripps
- Unit rules
- Contact hours
- 3 hours per week
- The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
- All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
- Unit readings, including any essential textbooks, are listed in the unit outline for each unit, one week prior the commencement of study. The unit outline will be available via the LMS and the UWA Handbook one week prior the commencement of study. Reading lists and essential textbooks are subject to change each semester. Information on essential textbooks will also be made available on the Essential Textbooks. This website is updated regularly in the lead up to semester so content may change. It is recommended that students purchase essential textbooks for convenience due to the frequency with which they will be required during the unit. A limited number of textbooks will be made available from the Library in print and will also be made available online wherever possible. Essential textbooks can be purchased from the commercial vendors to secure the best deal. The Student Guild can provide assistance on where to purchase books if required. Books can be purchased second hand at the Guild Secondhand bookshop (second floor, Guild Village), which is located on campus.