PUN105 Health Statistics
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | PUN105 |
|---|---|
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $555 |
| Domestic tuition unit fee | $3,348 |
| International unit fee | $4,392 |
Unit Outline: Semester 2 2024, Kelvin Grove, Internal
| Unit code: | PUN105 |
|---|---|
| Credit points: | 12 |
| Coordinators: | Michelle Gatton | m.gatton@qut.edu.au |
Overview
This is a foundational research methods unit which introduces fundamental statistical concepts relevant to describing data and testing scientific hypotheses. An understanding of basic statistical concepts is a fundamental research skill in any scientific or health discipline. Such knowledge is mandatory for critical evaluation of the research literature, for design of efficient research studies, and to inform appropriate interpretation of research results. As such, the concepts taught in this unit are essentail for postgraduate students intending to undertake independent research, and indeed, to any student attempting to critically evaluate research literature. This is an introductory unit and knowledge and skills developed in this unit are relevant to a variety of health disciplines. HLN709 (Advanced Epidemiology and Biostatistics) builds on this unit by extending your knowledge and skills, allowing you to conduct more complex analysis.
Learning Outcomes
On successful completion of this unit you will be able to:
- Discriminate the most appropriate descriptive and inferential statistics to use in a given health context;
- Analyse health data using statistical software and interrogate the test assumptions;
- Interpret and report the results of computer-generated statistical analyses.
Content
Beyond a common core of statistical concepts, each discipline area emphasises its own set of descriptive and inferential statistical methods and even terminology. The content of this unit emphasises both core and health-specific statistical methods in the health sciences. Students will be provided with substantial practical experience in the application and interpretation of the most common statistical methods to health data, and will also be made aware of data management principles in preparation for analysis. Rather than introducing a variety of statistical methods, this unit will be aimed at mastery of a few fundamental concepts including descriptive statistics, Chi-square analysis, comparison of means and linear regression. This level of mastery is considered imperative whether or not students continue on to postgraduate research. There will be a strong emphasis on applying concepts through worked examples from a range of topic areas, and interpreting and reporting results.
Learning Approaches
This unit engages you in your learning through a theory-to-practice approach. You will develop a theoretical understanding of concepts by engaging with pre-recorded content, with practical application in tutorials where you will analyse real data sets.
The unit adopts a blended learning approach. Internal students will engage with online resources and participate in a tutorial each week where you will work with peers and teaching staff. Online students will access the same online resources and apply these learnings by completing an activity workbook. Formative online learning activities will be available to all students.
Feedback on Learning and Assessment
You will gain feedback in this unit by participating in tutorials and online discussions. Written feedback, either as worked solutions and/or individual feedback, will be provided for each assessment task. Formative online resources are available to provide feedback prior to Assessment 1.
Assessment
Overview
The successful study of statistics requires cumulative learning. This unit is designed to reflect this, and hence mastery of early concepts will be necessary to understand later concepts. Assessment items are similarly designed, where understanding of some concepts will, of necessity, be assessed (at different levels) in every assessment item. All assessment items have been designed to be both formative and summative. You will do a self-assessment during Welcome Week designed by the Student Success Group to help understand your entry numerical skills and receive targeted support where required.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Exam
Open-book examination including a practical task to assess comprehension of basic concepts and application to new problems in a given health context. The exam will typically have 7 multiple choice questions (worth 7/40 marks), 5 multiple answer questions with negative marking (worth 12/40 marks), 1 matching question (worth 3/40 marks), 2 numeric/calculation questions (worth 6/40 marks) and 2 short answer questions (worth 12/40 marks). This question composition may change between unit offerings, but will never have no more than 50% of questions being multiple choice.
Assessment: Analytical Report
You will assume the role of a data analyst in a hypothetical, interdisciplinary research project team and analyse real-world data to answer pre-defined research questions. You will document your approach and results in the format of an analytical report which the research team can use as the basis for a journal article.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Students are expected to engage in learning and assessment at QUT with honesty, transparency and fairness. Maintaining academic integrity means upholding these principles and demonstrating valuable professional capabilities based on ethical foundations.
Failure to maintain academic integrity can take many forms. It includes cheating in examinations, plagiarism, self-plagiarism, collusion, and submitting an assessment item completed by another person (e.g. contract cheating). It can also include providing your assessment to another entity, such as to a person or website.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Further details of QUT’s approach to academic integrity are outlined in the Academic integrity policy and the Student Code of Conduct. Breaching QUT’s Academic integrity policy is regarded as student misconduct and can lead to the imposition of penalties ranging from a grade reduction to exclusion from QUT.
Resources
Resource Materials
Recommended text(s)
Kirkwood, B.R., Sterne J.A. (2003). Essential Medical Statistics. Blackwell: USA.
Other
The PUN105 Study Guide is a recommended resource for all students. Both internal and online students will be able to download the study guide modules from the PUN105 Canvas website. Required readings will be made available to all students via QUT Readings.
Students will be required to have access to a statistical software package. The unit notes and examples will use the Jamovi statistical software. This is freeware and available for free download by all students.
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit. You are recommended to take regular breaks if engaging in prolonged computer-based work.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.NS95 Master of Nursing
- Apply advanced knowledge and skills to manage and improve nursing practices across diverse and complex contexts to improve health outcomes and service provision.
Relates to: Analytical Report - Critically analyse evidence to inform decision-making in advanced nursing and interprofessional care contexts.
Relates to: Exam, Analytical Report - Communicate complex evidence-based findings through professional dissemination using a range of digital technologies.
Relates to: Analytical Report
PU60 Graduate Diploma in Public Health
- Apply knowledge of public health principles to current public health issues in diverse local and international contexts
Relates to: Exam - Critically analyse and synthesise the specialised knowledge, theories and frameworks of public health practice
Relates to: Analytical Report - Apply advanced oral, written and technical communication and academic skills to professional practice
Relates to: Analytical Report - Promote efficient and equitable gains in population health through culturally-safe, evidence-based practice.
Relates to: Analytical Report
PU86 Master of Public Health
- Apply advanced knowledge of public health principles to complex, current public health issues in diverse local and international contexts
Relates to: Exam - Critically analyse, synthesise and apply the specialised knowledge,theories and frameworks of public health practice
Relates to: Analytical Report - Apply advanced oral,written and technical communication and research literacy skills to professional practice in interprofessional teams
Relates to: Analytical Report - Engage professionally to advance efficient and equitable gains in population health through leadership and culturally-safe, evidence-based practice.
Relates to: Analytical Report
Unit Outline: Semester 2 2024, Online
| Unit code: | PUN105 |
|---|---|
| Credit points: | 12 |
Overview
This is a foundational research methods unit which introduces fundamental statistical concepts relevant to describing data and testing scientific hypotheses. An understanding of basic statistical concepts is a fundamental research skill in any scientific or health discipline. Such knowledge is mandatory for critical evaluation of the research literature, for design of efficient research studies, and to inform appropriate interpretation of research results. As such, the concepts taught in this unit are essentail for postgraduate students intending to undertake independent research, and indeed, to any student attempting to critically evaluate research literature. This is an introductory unit and knowledge and skills developed in this unit are relevant to a variety of health disciplines. HLN709 (Advanced Epidemiology and Biostatistics) builds on this unit by extending your knowledge and skills, allowing you to conduct more complex analysis.
Learning Outcomes
On successful completion of this unit you will be able to:
- Discriminate the most appropriate descriptive and inferential statistics to use in a given health context;
- Analyse health data using statistical software and interrogate the test assumptions;
- Interpret and report the results of computer-generated statistical analyses.
Content
Beyond a common core of statistical concepts, each discipline area emphasises its own set of descriptive and inferential statistical methods and even terminology. The content of this unit emphasises both core and health-specific statistical methods in the health sciences. Students will be provided with substantial practical experience in the application and interpretation of the most common statistical methods to health data, and will also be made aware of data management principles in preparation for analysis. Rather than introducing a variety of statistical methods, this unit will be aimed at mastery of a few fundamental concepts including descriptive statistics, Chi-square analysis, comparison of means and linear regression. This level of mastery is considered imperative whether or not students continue on to postgraduate research. There will be a strong emphasis on applying concepts through worked examples from a range of topic areas, and interpreting and reporting results.
Learning Approaches
This unit engages you in your learning through a theory-to-practice approach. You will develop a theoretical understanding of concepts by engaging with pre-recorded content, with practical application in tutorials where you will analyse real data sets.
The unit adopts a blended learning approach. Internal students will engage with online resources and participate in a tutorial each week where you will work with peers and teaching staff. Online students will access the same online resources and apply these learnings by completing an activity workbook. Formative online learning activities will be available to all students.
Feedback on Learning and Assessment
You will gain feedback in this unit by participating in tutorials and online discussions. Written feedback, either as worked solutions and/or individual feedback, will be provided for each assessment task. Formative online resources are available to provide feedback prior to Assessment 1.
Assessment
Overview
The successful study of statistics requires cumulative learning. This unit is designed to reflect this, and hence mastery of early concepts will be necessary to understand later concepts. Assessment items are similarly designed, where understanding of some concepts will, of necessity, be assessed (at different levels) in every assessment item. All assessment items have been designed to be both formative and summative. You will do a self-assessment during Welcome Week designed by the Student Success Group to help understand your entry numerical skills and receive targeted support where required.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Exam
Open-book examination including a practical task to assess comprehension of basic concepts and application to new problems in a given health context. The exam will typically have 7 multiple choice questions (worth 7/40 marks), 5 multiple answer questions with negative marking (worth 12/40 marks), 1 matching question (worth 3/40 marks), 2 numeric/calculation questions (worth 6/40 marks) and 2 short answer questions (worth 12/40 marks). This question composition may change between unit offerings, but will never have no more than 50% of questions being multiple choice.
Assessment: Analytical Report
You will assume the role of a data analyst in a hypothetical, interdisciplinary research project team and analyse real-world data to answer pre-defined research questions. You will document your approach and results in the format of an analytical report which the research team can use as the basis for a journal article.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Students are expected to engage in learning and assessment at QUT with honesty, transparency and fairness. Maintaining academic integrity means upholding these principles and demonstrating valuable professional capabilities based on ethical foundations.
Failure to maintain academic integrity can take many forms. It includes cheating in examinations, plagiarism, self-plagiarism, collusion, and submitting an assessment item completed by another person (e.g. contract cheating). It can also include providing your assessment to another entity, such as to a person or website.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Further details of QUT’s approach to academic integrity are outlined in the Academic integrity policy and the Student Code of Conduct. Breaching QUT’s Academic integrity policy is regarded as student misconduct and can lead to the imposition of penalties ranging from a grade reduction to exclusion from QUT.
Resources
Resource Materials
Recommended text(s)
Kirkwood, B.R., Sterne J.A. (2003). Essential Medical Statistics. Blackwell: USA.
Other
The PUN105 Study Guide is a recommended resource for all students. Both internal and online students will be able to download the study guide modules from the PUN105 Canvas website. Required readings will be made available to all students via QUT Readings.
Students will be required to have access to a statistical software package. The unit notes and examples will use the Jamovi statistical software. This is freeware and available for free download by all students.
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit. You are recommended to take regular breaks if engaging in prolonged computer-based work.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.NS95 Master of Nursing
- Apply advanced knowledge and skills to manage and improve nursing practices across diverse and complex contexts to improve health outcomes and service provision.
Relates to: Analytical Report - Critically analyse evidence to inform decision-making in advanced nursing and interprofessional care contexts.
Relates to: Exam, Analytical Report - Communicate complex evidence-based findings through professional dissemination using a range of digital technologies.
Relates to: Analytical Report
PU60 Graduate Diploma in Public Health
- Apply knowledge of public health principles to current public health issues in diverse local and international contexts
Relates to: Exam - Critically analyse and synthesise the specialised knowledge, theories and frameworks of public health practice
Relates to: Analytical Report - Apply advanced oral, written and technical communication and academic skills to professional practice
Relates to: Analytical Report - Promote efficient and equitable gains in population health through culturally-safe, evidence-based practice.
Relates to: Analytical Report
PU86 Master of Public Health
- Apply advanced knowledge of public health principles to complex, current public health issues in diverse local and international contexts
Relates to: Exam - Critically analyse, synthesise and apply the specialised knowledge,theories and frameworks of public health practice
Relates to: Analytical Report - Apply advanced oral,written and technical communication and research literacy skills to professional practice in interprofessional teams
Relates to: Analytical Report - Engage professionally to advance efficient and equitable gains in population health through leadership and culturally-safe, evidence-based practice.
Relates to: Analytical Report