STAT465-18S2 (C) Semester Two 2018

Advanced Data Analysis and Statistical Consulting

15 points

Details:
Start Date: Monday, 16 July 2018
End Date: Sunday, 18 November 2018
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Friday, 27 July 2018
  • Without academic penalty (including no fee refund): Friday, 12 October 2018

Description

This course teaches students to apply the statistical methods in a variety of practical situations, to communicate in an interdisciplinary environment, to provide critique and respond to it.

In most undergraduate courses, you are taught the theory behind a method and then given neat examples to which it can be applied and software to apply it. In reality, the most common question you will hear from a non-statistician is ’how do I analyse my data? So you are the one who has to come up with the appropriate research question and choose the suitable method (and sometimes learn it quickly too) . It is common in real world applications for the experiments have not been well planned and for data to be missing, which will need to be taken it into account.

The assumptions underlying the statistical model (e.g. homoscedasticity and normally distributed) often do not hold and you will have to know what to do. Finally, your fellow scientists, laymen and policymakers are all interested in different aspects of the research question and that is rarely the statistical significance of your ANOVA: you have to know how to communicate your results clearly, correctly and efficiently and how to defend your choices in data analysis and collection.

This course is about the reality of being an applied statistician. Besides covering the above points in class, individual statistical consulting session will provide you with hands-on experience.

Good knowledge of multivariate statistical methods, GLMs, and basic sampling theory expected. Working knowledge of R is recommended for forecasting methods. It provides extensive training in forcasting and modelling techniques such as smoothing, dynamic regressions, multivariate autoregressions, state space models, and neural networks with a wide range of applications.

Prerequisites

STAT315, and one of (STAT314, STAT317, STAT319)

Course Coordinator

For further information see Mathematics and Statistics Head of Department

Indicative Fees

Domestic fee $905.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All STAT465 Occurrences

  • STAT465-18S2 (C) Semester Two 2018