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Study masters degree online through Open Universities Australia. Explore all degrees, subjects and short courses now.

UniSQ&#39;s Master of Science (Mathematics and Statistics) is ideal for graduates from any discipline who are looking to develop their mathematics/statistics knowledge and skills. Even if you haven’t studied in some time, this degree will provide you with an in-depth education in mathematical and/or statistical techniques and problem solving skills. Examine the fundamentals of theoretical and applied statistics, mathematical modelling and operations research, and computing and coding skills. This degree incorporates practical methods for undertaking analysis, modelling and evidence-based, data-driven decision-making.

Master of Science (Mathematics and Statistics)

Data and Analysis

Introduction to Psychological Design and Statistics

Data Analysis for Business

Statistics

Research Design

HR Analytics

Quantitative Methods for Social Research

UO R for Data Analytics

Statistical Concepts for Science

Basic Statistical Computing Using R

This subject introduces R, one of the popular open source statistical programming languages commonly used in applied statistics and data science disciplines. Students will learn key programming principles of R and develop competence in programming in R which are essential for a statistician or data scientist to perform different types of statistical analyses.This subject was formerly known as STA60003 Basic Statistical Computing

Upskill and package up your computer and statistical knowledge. Form questions. Use SPSS software to select, modify, merge and apply data visualisation techniques. Investigate missing values and manage complex data files. 

This subject extends the ideas developed in Statistical Practice 1 to include more advanced analyses, broaden the range of applications students are familiar with so that they will be able to carry out independent statistical investigations, and develop an awareness of the assumptions and limitations involved in the generalisation of results of such investigations.

Practice and advance your statistical knowledge and extend ideas. Produce an independent investigation. Get analytical and compare groups using parametric and non-parametric methods. Stop generalising, question assumptions and identify data limits. 

Statistical Practice 2

This subject teaches students to identify some of the methodologies used in survey research. It includes an overview of the procedures used in survey research, a descriptive approach to methods including questionnaire design, data collection, and an introduction to survey sampling. It covers ethics and laws in conducting research. It also covers topics related to incidence and prevalence, standardisation, different types of study designs including cohort and case-control studies, randomised control trials and clinical trials in health statistics and elsewhere. Case studies will be drawn from areas such as sociology, market research, psychology, medical sciences and other areas as appropriate.

Survey research methods and get critical about design. Describe approaches and observe techniques. Sample data collection methods. Scale and graph procedures and figure out incidence and prevalence. Draw on case studies and assess and present data

This subject develops students’ understanding of a range of statistical methods along with their assumptions and limitations of their application. It enables students to develop the capacity to carry out independent statistical analysis of data using a standard statistical software package and also aims to develop students’ abilities in effectively communicating the outcomes of statistical investigations. In addition, it will provide a foundation and motivation for exposure to statistical ideas subsequent to the Graduate Certificate (GC) degree.

Develop a number of statistical data techniques; assess theories and survey limitations. Increase analysis skills and translate investigation outcomes. Recognise statistical inference and sampling distributions. Transcribe interpretative summaries. 

Statistical Practice 1

The ability to make sound decisions in High Performance Sport is critical to maximizing performance outcomes. In order to do this, practitioners need specific knowledge and skills in data analysis techniques, in addition to the ability to present data in a meaningful way to a variety of audiences. This subject is based on contemporary data analysis techniques focusing on determining practically meaningful differences in athletic performance. A range of approaches will be explored to allow for analysis of both individual and group data. The aim of this subject is to provide students with the knowledge, understanding and skills to analyse and interpret data of relevance to sports science and athletic performance and effectively present the results.

Data Analysis and Interpretation for High Performance

Masters Degree Statistics Courses & Degrees | Open Universities Australia

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