|Faculty or Section :||Faculty of Health, Engineering and Sciences|
|School or Department :||School of Mathematics, Physics & Computing|
|Grading basis :||Graded|
|Course fee schedule :||https://www.unisq.edu.au/current-students/administration/fees/fee-schedules|
Enrolment is not permitted in STA2100 if STA3100 has been previously completed.
An understanding of our society relies on the collection, analysis, interpretation, and dissemination of information about the people within our society. This course introduces basic concepts relevant to the effective collection, analysis, and interpretation of quantitative information from individuals and groups of individuals. An understanding of these concepts is essential to students in behavioural sciences, health sciences, educational studies, sociology, humanities, political science, business and management studies, legal studies, journalism and any discipline involving the initiation or critical appraisal of studies of social phenomena. Active participants should obtain enough knowledge to understand and critically analyse reports of many social science studies and develop sufficient practical skills to interpret information produced by a statistical software package. This course provides the foundations for application and further development in a range of programs.
Students are introduced to basic concepts and tools commonly involved in collecting, managing, summarizing, analysing, interpreting, and presenting quantitative data. No prior statistical or mathematical knowledge is assumed. Methods of descriptive and inferential statistics are introduced. Issues related to causation and confounding; the nature of variability, the reliability of summary statistics, the limitations and assumptions underpinning statistical techniques; the appropriate use of language in interpreting an analysis; and the use of computer output in understanding data summary and analysis are explored. The emphasis is on the concepts, interpretations, and applications of statistics as used in the analysis of data, rather than on mathematical or computational aspects. The use of case studies is emphasised and writing of reports facilitated.
|Semester 2, 2022||Online|