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.
Swinburne University of Technology leads the way with innovative and new ways of teaching, learning and thinking. It offers a wide range of study options, from pre-apprenticeships, undergraduate, postgraduate and PhDs, including online degrees with Open Universities Australia. Swinburne is known for career-oriented education and encouraging lifelong learning.
Students who successfully complete this subject will be able to:
Effectively display information in datasets graphically
Select an appropriate descriptive or inferential statistical technique based on the researcher’s hypothesis, the level of measurement of the variables and testing of the appropriate assumptions to analyse the data
Select appropriate IBM SPSS Statistics procedures, Java applets on the web and mathematical calculations, to obtain basic statistical test results, including confidence intervals and effect size statistics
Explain the foundations of statistical inference, in particular the role of sampling distributions and the use of the normal distribution as a density curve
Recognize when more advanced techniques are needed
Write interpretive summary reports for both descriptive and inferential statistical analysis.
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.