MZB103 Introduction to 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: | MZB103 |
|---|---|
| Antirequisite(s): | SEB113 |
| Credit points: | 6 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $289 |
| Domestic tuition unit fee | $1,764 |
| International unit fee | $2,316 |
Unit Outline: Semester 1 - 6 Week A 2025, Gardens Point, Internal
| Unit code: | MZB103 |
|---|---|
| Credit points: | 6 |
| Anti-requisite: | SEB113 |
| Coordinator: | Helen Thompson | helen.thompson@qut.edu.au |
Overview
MZB103 is a foundational science unit for developing core skills in statistics that underpins all modern scientific practice and covers topics relevant to later science units. Thus this unit serves as a foundation and prerequisite for many subsequent units in the science degree. The applied approach in this unit develops topics through examples in science which are accessible to students from a range of disciplines.
Learning Outcomes
On successful completion of this unit you will be able to:
- Recall core foundational statistics concepts and translate them to new scientific contexts
- Critically select and apply statistical techniques and interpret statistical outputs to solve scientific problems
- Communicate in written and graphical formats to scientists and the broader community using appropriate conventions
Content
In this unit you will explore the following topics:
- Distributions and uncertainty
- Scientific investigation
- t-test
- Non-parametric tests for medians
- Frequency and proportion
- Experimental design
Note: This unit does not teach or assess coding skills, but use of R statistical software is required to support statistics learning.
Learning Approaches
The total volume of learning in MZB103 is 75 hours, as per the Australian Qualifications Framework that describes how long a student who does not possess any of the unit competencies would take to develop all the required skills and knowledge. An example breakdown of this 75 hours is:
- 12 hours (2 hours x 6 weeks) lecture classes
- 12 hours (2 hours x 6 weeks) practical classes
- 27 hours self-directed independent learning (4.5 hours x 6 weeks)
- 6 hours formative assessment (1 hour x 6 weeks formative quizzes)
- 18 hours summative assessment (2 hours x 4 weeks statistics portfolio contributions, 8.5 hours exam preparation, 1.5 hour exam)
This unit follows the 'I do (teacher), we do (teacher and student), you do (student)' model of learning through the demonstration of an example in the lecture (I do), followed by collaborative solving of a similar example in the practical class (we do) and then independent individual solving of a further similar example that forms part of your portfolio assessment (you do).
The sequence of learning, assessment and feedback activities each week is as follows. Students complete the activities in the order listed.
- Pre-Lecture Reading and Poll: Complete required reading before the lecture. Submit response to optional short online poll to let teaching staff know aspects of the required reading you would like explained. (1 hour suggested)
- Lecture Class: Face-to-face on-campus interactive class. Core concepts will be discussed and examples demonstrated to support development of knowledge and skills. (2 hours)
- Pre-Practical Review: Review the required reading and lecture to consolidate learning prior to practical class. (1 hour suggested)
- Practical Class: Face-to-face on-campus class. Modern industry-relevant statistical software (R statistical software) will be introduced and used as a tool to support statistics learning. Practical classes are designed around worksheets that contain questions to be attempted, including several questions that will form the weekly portfolio assessment contribution. Examples will be demonstrated and students encouraged to participate in solving the demonstration problems. Students then work on worksheet problems with assistance from teaching staff. Collaborative learning with your teacher and peers is encouraged, however assessment (portfolio) questions must be attempted individually. (2 hours)
- Pre-Assessment Review: Complete and review the practical worksheet to further consolidate learning. (2 hours suggested)
- In-Semester Assessment: Attempt the weekly online formative quiz for feedback to regularly self-assess learning. Complete the worksheet questions that form part of the summative portfolio assessment. The quizzes and portfolios form exemplars for the end-of-teaching-period exam, end of teaching period revision of these should form part of your exam preparation. (1 hour formative quiz, 2 hours summative portfolio suggested)
Attend optional MZB103 support sessions (see https://canvas.qut.edu.au/courses/12591/pages/stem-support-for-science-students) in addition to lecture and practical classes, as needed throughout teaching period to support your self-directed independent learning. FREE STEM Support for Science Students workshops are also available throughout the year.
Feedback on Learning and Assessment
Practical classes: Teaching staff circulate around the class to support you when attempting worksheet questions. Discussion with teaching staff during practical classes forms part of feedback on your learning. You are encouraged to collaborate with your peers to solve worksheet questions that do not form part of your summative (portfolio) assessment. Collaborative peer discussion is implicit feedback that is useful for informing your skills and knowledge development.
Summative assessment: Your mark on your assessment provides feedback on your level of attainment of the unit learning outcomes. You will also be provided with brief written feedback on your individual portfolio submissions, and be given broader verbal class feedback during the lecture. You can request more detailed feedback on your marked portfolio submissions as needed from your teacher during your practical class. Exam feedback is available during the review of grade period by appointment with the unit coordinator.
Formative assessment: Online quizzes will provide automated feedback in the form of your mark for each question and automated feedback comments that allow you to self-assess your learning. You can also request feedback on your quiz attempts during your practical class as needed.
Solutions to problems: Solutions to quiz questions, portfolio questions and other worksheet questions allow you to self-assess your learning by comparing your attempts to the solutions.
MZB103 online communication channel: An online communication channel will be available for you to engage with your peers. At least once per week, teaching staff will review the communication channel, confirm or correct information posted by students, and respond to any outstanding questions. Participation in the online communication channel will provide a way for you to receive and give feedback through posting questions, answering questions and reviewing posts.
Assessment
Overview
The assessment items in this unit are designed to determine your level of competency in meeting the unit learning outcomes while providing you with a range of tasks with varying levels of skill development and difficulty.
Weekly Online Quiz (Formative Only)
Weight: 0%
Individual or Group: Individual
Unit Learning Outcomes: ULO1
Formative weekly online multiple choice quizzes with automated feedback will be available, in addition to the summative portfolio assessment, to support your learning. Unlimited attempts are permitted. These quizzes are designed to allow you to self-assess your understanding of foundational statistics concepts. The quiz questions are exemplars for the multiple choice questions on the examination. This is formative-only assessment, the marks do not contribute to your final grade and do not need to be submitted.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Statistics Portfolio
The portfolio assesses content from weeks 1-4. The portfolio questions will be a selection of questions from practical class worksheets. You will submit your portfolio in week 3 (covering content from weeks 1-2) and in week 5 (covering content from weeks 3-4). The portfolio questions form exemplars for the short answer questions on the examination.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Examination (invigilated)
The examination will cover all content (content from weeks 1-6), and assess understanding, application and interpretation of foundational statistics concepts, techniques and models to solve scientific problems.
The examination will consist of 2 sections:
- Section A: Multiple Choice
- Section B: Short Answer
The formative online quizzes form the exemplars for Section A. The statistics portfolio and practical class worksheets form exemplars for Section B.
You will not be permitted to take a resource sheet into the examination, the examination paper will instead contain a formula sheet, which is the same formula sheet provided to you at the beginning of the teaching period. You are encouraged to use and familiarise yourself with the formula sheet during the teaching period, prior to your examination. You will be permitted to use a calculator of any type.
The examination will require attendance on QUT campus. The late submission period does not apply, and no extensions are available. if you can’t attend this exam due to special circumstances, you may apply to sit a deferred exam.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
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.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Requirements to Study
Costs
There are no out of the ordinary costs associated with the study of this unit.
Resources
Required readings for MZB103 will consist of lecture materials provided on Canvas. Recommended readings will also be provided from the recommended text listed below.
There are many reference texts for this unit, many of which can be located in the library. There are also many online resources such as lecture notes and some e-books that can be found online. Example reference texts are listed below.
All statistical computation will be performed with R statistical software inside the RStudio integrated development environment. Both of these pieces of software are required, are available in QUT computer labs and are available online at no charge for students to install on their personal computers.
Resource Materials
Recommended text(s)
Currell, G & Downman, A (2009) Essential Mathematics and Statistics for Science (2nd ed.) Wiley-Blackwell, Oxford.
Available to view online through QUT Library.
Reference book(s)
Ekstrom, C (2019) R Primer (2nd ed.) Taylor and Francis, Boca Raton, Florida.
Available to view online through QUT Library.
Software
R Statistical Software download for free
RStudio Integrated Development Environment (IDE) download for free
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit, as all classes will be held in ordinary lecture theatres and computer laboratories. Emergency exits and assembly areas will be pointed out in the first few lectures. You are referred to the University policy on health and safety.
http://www.mopp.qut.edu.au/A/A_09_01.jsp
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.ST01 Bachelor of Science
- Develop a broad, multidisciplinary understanding of science and a specialised, in-depth knowledge of at least one discipline.
Relates to: ULO1, ULO2, Statistics Portfolio, Examination (invigilated) - Use higher order thinking skills to design, plan, and conduct investigations and evaluate data to address scientific questions and challenges.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Develop and demonstrate key competencies in scientific practices and relevant technologies.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Communicate scientific findings, concepts and evidence-based reasoning to diverse audiences using a variety of methods.
Relates to: ULO3, Statistics Portfolio
SV02 Bachelor of Science
- Develop a broad, multidisciplinary understanding of science and a specialised, in-depth knowledge of at least one discipline.
Relates to: ULO1, ULO2, Statistics Portfolio, Examination (invigilated) - Use higher order thinking skills to design, plan, and conduct investigations and evaluate data to address scientific questions and challenges.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Develop and demonstrate key competencies in scientific practices and relevant technologies.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Communicate scientific findings, concepts and evidence-based reasoning to diverse audiences using a variety of methods.
Relates to: ULO3, Statistics Portfolio
Unit Outline: Semester 2 - 6 Week C 2025, Gardens Point, Internal
| Unit code: | MZB103 |
|---|---|
| Credit points: | 6 |
| Anti-requisite: | SEB113 |
Overview
MZB103 is a foundational science unit for developing core skills in statistics that underpins all modern scientific practice and covers topics relevant to later science units. Thus this unit serves as a foundation and prerequisite for many subsequent units in the science degree. The applied approach in this unit develops topics through examples in science which are accessible to students from a range of disciplines.
Learning Outcomes
On successful completion of this unit you will be able to:
- Recall core foundational statistics concepts and translate them to new scientific contexts
- Critically select and apply statistical techniques and interpret statistical outputs to solve scientific problems
- Communicate in written and graphical formats to scientists and the broader community using appropriate conventions
Content
In this unit you will explore the following topics:
- Distributions and uncertainty
- Scientific investigation
- t-test
- Non-parametric tests for medians
- Frequency and proportion
- Experimental design
Note: This unit does not teach or assess coding skills, but use of R statistical software is required to support statistics learning.
Learning Approaches
The total volume of learning in MZB103 is 75 hours, as per the Australian Qualifications Framework that describes how long a student who does not possess any of the unit competencies would take to develop all the required skills and knowledge. An example breakdown of this 75 hours is:
- 12 hours (2 hours x 6 weeks) lecture classes
- 12 hours (2 hours x 6 weeks) practical classes
- 27 hours self-directed independent learning (4.5 hours x 6 weeks)
- 6 hours formative assessment (1 hour x 6 weeks formative quizzes)
- 18 hours summative assessment (2 hours x 4 weeks statistics portfolio contributions, 8.5 hours exam preparation, 1.5 hour exam)
This unit follows the 'I do (teacher), we do (teacher and student), you do (student)' model of learning through the demonstration of an example in the lecture (I do), followed by collaborative solving of a similar example in the practical class (we do) and then independent individual solving of a further similar example that forms part of your portfolio assessment (you do).
The sequence of learning, assessment and feedback activities each week is as follows. Students complete the activities in the order listed.
- Pre-Lecture Reading and Poll: Complete required reading before the lecture. Submit response to optional short online poll to let teaching staff know aspects of the required reading you would like explained. (1 hour suggested)
- Lecture Class: Face-to-face on-campus interactive class. Core concepts will be discussed and examples demonstrated to support development of knowledge and skills. (2 hours)
- Pre-Practical Review: Review the required reading and lecture to consolidate learning prior to practical class. (1 hour suggested)
- Practical Class: Face-to-face on-campus class. Modern industry-relevant statistical software (R statistical software) will be introduced and used as a tool to support statistics learning. Practical classes are designed around worksheets that contain questions to be attempted, including several questions that will form the weekly portfolio assessment contribution. Examples will be demonstrated and students encouraged to participate in solving the demonstration problems. Students then work on worksheet problems with assistance from teaching staff. Collaborative learning with your teacher and peers is encouraged, however assessment (portfolio) questions must be attempted individually. (2 hours)
- Pre-Assessment Review: Complete and review the practical worksheet to further consolidate learning. (2 hours suggested)
- In-Semester Assessment: Attempt the weekly online formative quiz for feedback to regularly self-assess learning. Complete the worksheet questions that form part of the summative portfolio assessment. The quizzes and portfolios form exemplars for the end-of-teaching-period exam, end of teaching period revision of these should form part of your exam preparation. (1 hour formative quiz, 2 hours summative portfolio suggested)
Attend optional MZB103 support sessions (see https://canvas.qut.edu.au/courses/12591/pages/stem-support-for-science-students) in addition to lecture and practical classes, as needed throughout teaching period to support your self-directed independent learning. FREE STEM Support for Science Students workshops are also available throughout the year.
Feedback on Learning and Assessment
Practical classes: Teaching staff circulate around the class to support you when attempting worksheet questions. Discussion with teaching staff during practical classes forms part of feedback on your learning. You are encouraged to collaborate with your peers to solve worksheet questions that do not form part of your summative (portfolio) assessment. Collaborative peer discussion is implicit feedback that is useful for informing your skills and knowledge development.
Summative assessment: Your mark on your assessment provides feedback on your level of attainment of the unit learning outcomes. You will also be provided with brief written feedback on your individual portfolio submissions, and be given broader verbal class feedback during the lecture. You can request more detailed feedback on your marked portfolio submissions as needed from your teacher during your practical class. Exam feedback is available during the review of grade period by appointment with the unit coordinator.
Formative assessment: Online quizzes will provide automated feedback in the form of your mark for each question and automated feedback comments that allow you to self-assess your learning. You can also request feedback on your quiz attempts during your practical class as needed.
Solutions to problems: Solutions to quiz questions, portfolio questions and other worksheet questions allow you to self-assess your learning by comparing your attempts to the solutions.
MZB103 online communication channel: An online communication channel will be available for you to engage with your peers. At least once per week, teaching staff will review the communication channel, confirm or correct information posted by students, and respond to any outstanding questions. Participation in the online communication channel will provide a way for you to receive and give feedback through posting questions, answering questions and reviewing posts.
Assessment
Overview
The assessment items in this unit are designed to determine your level of competency in meeting the unit learning outcomes while providing you with a range of tasks with varying levels of skill development and difficulty.
Weekly Online Quiz (Formative Only)
Weight: 0%
Individual or Group: Individual
Unit Learning Outcomes: ULO1
Formative weekly online multiple choice quizzes with automated feedback will be available, in addition to the summative portfolio assessment, to support your learning. Unlimited attempts are permitted. These quizzes are designed to allow you to self-assess your understanding of foundational statistics concepts. The quiz questions are exemplars for the multiple choice questions on the examination. This is formative-only assessment, the marks do not contribute to your final grade and do not need to be submitted.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Statistics Portfolio
The portfolio assesses content from weeks 1-4. The portfolio questions will be a selection of questions from practical class worksheets. You will submit your portfolio in week 3 (covering content from weeks 1-2) and in week 5 (covering content from weeks 3-4). The portfolio questions form exemplars for the short answer questions on the examination.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Examination (invigilated)
The examination will cover all content (content from weeks 1-6), and assess understanding, application and interpretation of foundational statistics concepts, techniques and models to solve scientific problems.
The examination will consist of 2 sections:
- Section A: Multiple Choice
- Section B: Short Answer
The formative online quizzes form the exemplars for Section A. The statistics portfolio and practical class worksheets form exemplars for Section B.
You will not be permitted to take a resource sheet into the examination, the examination paper will instead contain a formula sheet, which is the same formula sheet provided to you at the beginning of the teaching period. You are encouraged to use and familiarise yourself with the formula sheet during the teaching period, prior to your examination. You will be permitted to use a calculator of any type.
The examination will require attendance on QUT campus. The late submission period does not apply, and no extensions are available. if you can’t attend this exam due to special circumstances, you may apply to sit a deferred exam.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
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.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Requirements to Study
Costs
There are no out of the ordinary costs associated with the study of this unit.
Resources
Required readings for MZB103 will consist of lecture materials provided on Canvas. Recommended readings will also be provided from the recommended text listed below.
There are many reference texts for this unit, many of which can be located in the library. There are also many online resources such as lecture notes and some e-books that can be found online. Example reference texts are listed below.
All statistical computation will be performed with R statistical software inside the RStudio integrated development environment. Both of these pieces of software are required, are available in QUT computer labs and are available online at no charge for students to install on their personal computers.
Resource Materials
Recommended text(s)
Currell, G & Downman, A (2009) Essential Mathematics and Statistics for Science (2nd ed.) Wiley-Blackwell, Oxford.
Available to view online through QUT Library.
Reference book(s)
Ekstrom, C (2019) R Primer (2nd ed.) Taylor and Francis, Boca Raton, Florida.
Available to view online through QUT Library.
Software
R Statistical Software download for free
RStudio Integrated Development Environment (IDE) download for free
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit, as all classes will be held in ordinary lecture theatres and computer laboratories. Emergency exits and assembly areas will be pointed out in the first few lectures. You are referred to the University policy on health and safety.
http://www.mopp.qut.edu.au/A/A_09_01.jsp
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.ST01 Bachelor of Science
- Develop a broad, multidisciplinary understanding of science and a specialised, in-depth knowledge of at least one discipline.
Relates to: ULO1, ULO2, Statistics Portfolio, Examination (invigilated) - Use higher order thinking skills to design, plan, and conduct investigations and evaluate data to address scientific questions and challenges.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Develop and demonstrate key competencies in scientific practices and relevant technologies.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Communicate scientific findings, concepts and evidence-based reasoning to diverse audiences using a variety of methods.
Relates to: ULO3, Statistics Portfolio
SV02 Bachelor of Science
- Develop a broad, multidisciplinary understanding of science and a specialised, in-depth knowledge of at least one discipline.
Relates to: ULO1, ULO2, Statistics Portfolio, Examination (invigilated) - Use higher order thinking skills to design, plan, and conduct investigations and evaluate data to address scientific questions and challenges.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Develop and demonstrate key competencies in scientific practices and relevant technologies.
Relates to: ULO2, Statistics Portfolio, Examination (invigilated) - Communicate scientific findings, concepts and evidence-based reasoning to diverse audiences using a variety of methods.
Relates to: ULO3, Statistics Portfolio