Biostatistics for Health Sciences

• • Topics will include:
  • - Fundamental statistical concepts and methods
  • Types and levels of measurement of quantitative data and measures of central tendency and variability
  • Probability distributions
  • Hypothesis testing
  • Statistical confidence: confidence intervals, p-values, statistical effect sizes
  • Common statistical tests: comparison of means (between two or more dependent or independent groups), proportions
  • Variability and statistical inference;
  • - Application to health science practice
  • Key measures of association in health sciences: relative risk, attributable risk, odds ratios
  • Inferential statistics: correlation, linear regression, logistic regression, analysis of variance
  • Use of statistical software to analyse quantitative data sets: common statistical tests
  • Writing up statistical analyses: interpretation, requirements for expressing statistical results
  • Critical appraisal of statistical methods in health sciences research: common tools and approaches

Equivalent subjects

You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:

• ACU-PUBH620-Biostatistics

Additional requirements

• Software requirements - SPSS offered at a reduced cost to ACU students.

Understanding, using and interpreting statistics is crucial to health science research and practice, particularly in monitoring health outcomes and decision-making processes about interventions. This unit will develop students' knowledge of fundamental statistical concepts, such as descriptive and inferential statistics, common statistical tests and statistical methods frequently used in health science research. This will include hypothesis testing, estimation, associations, modelling relationships and prediction using different methods such as regression analyses. Throughout the unit, students will consolidate their understanding of statistical theory through its application to practice. While there are some formulae and computational elements to the unit, the emphasis is on interpretation and concepts. Besides the theoretical material, this unit will also enable students to run basic analyses using common statistical software. Using this software, students will analyse simulated health science data sets and then interpret the results obtained. This unit aims to extend students' statistical understanding and analytical expertise, which can then be applied to practice through critical appraisal statistical methods used in health science research.

A range of assessment procedures will be used to meet the unit learning outcomes and develop graduate attributes consistent with University assessment requirements. In order to successfully complete this unit, students need to complete and submit three graded assessment tasks and obtain an aggregate mark of greater than 50%. Assessment tasks for this unit have been designed to introduce students to the broad range of activity involved in biostatistics. In Assessment Task 1, students are required to demonstrate their understanding by analysing a health science data set. In Assessment Task 2, students are required to apply their biostatistical skills by preparing statistical methods and analysis for a peer reviewed journal article. Finally, in Assessment Task 3 students will critique and interpret the statistics in current published journal articles and reflect on how biostatistical knowledge will shape their professional practice.

• Analysis of simulated public data set - 2 parts (20%)
• Preparation of statistical methods and analysis for a peer-reviewed journal article. (40%)
• Biostatistics reflective practice and critique exercises (40%)

For textbook details check your university's handbook, website or learning management system (LMS).