SEB113 Quantitative Methods in Science

Coordinator

Name

Dr Belinda Spratt

Email

b.spratt@qut.edu.au

Phone

31383035

Rationale

The outstanding societal, economic, and environmental contribution of science to improving and prolonging humankind's existence is certainly rooted in its unique methodology. Quantitative methods play a key role in science. Therefore, this unit focuses on the fundamental mathematical and statistical approaches used routinely in science, with a particular emphasis on experimental data. It introduces analytical, modelling and simulation skills.
With reference to theory, field and experimental settings, you explore and develop practical problem-solving skills to quantify and model real problems in science.

Aims

The aim of this unit is to introduce you to and develop your quantitative skills of analysis, simulation and modelling which underpins all scientific practice. You will understand how quantitative techniques are applied in different science disciplines with the opportunity to investigate a problem or issue in a specific field. Computation is taught in a modern, free and open source computing environment in order to demonstrate the principles of data science and reproducible research.

Learning outcomes

On completion of this unit, you will provide evidence that you can:
1. Apply appropriate research methods, technologies and tools to inform scientific investigation.
2. Analyse, interpret, model and simulate numerical data for scientific purposes and problems.
3. Apply selected quantitative research methods and outcomes to solve scientific problems derived from theory, field and laboratory settings.
4. Evaluate scientific data and mathematical models to visualise their representation and communicate them to scientific peer groups and/or the broader community using appropriate conventions.

Content

The focus on this unit is on applying mathematical and statistical methods in scientific contexts. You will look for meaningful scientific 'patterns' in the data using mathematical functions, conduct data analysis using calculus, and model the data to increasing levels of complexity using algebra (equations). You will also learn how to select and apply appropriate quantitative methods in these contexts. We will refresh and deepen your understanding of statistical methods, functions, algebra and calculus which are fundamental to measurement in experimental science.

Approaches to teaching and learning

The focus of this unit is on learning and applying quantitative methods in science using data obtained from scientific observation, examples and practice in field, laboratory and theory settings. All quantitative (mathematical and statistical) knowledge and skills will be taught and practised in context, related to real examples, problems and observations. For this purpose, academic staff from mathematical and science fields will be working collaboratively to align scientific examples and applications for all quantitative methods so that you develop conceptual scientific understanding with quantitative skills. This will engage you to think and apply quantitative methods as a novice scientist with awareness of how different science disciplines use and represent data.
The unit adopts a blended learning approach consisting of a sequence of a two (2) hour lecture, a one (1) hour computer lab, and a two (2) hour collaborative workshop. Access to lecture, lab and workshop material is mediated by an adaptive release system, presenting students with pre-lecture preparatory material each week that aims to bridge the assumed knowledge and the week's lecture topic. The computer lab worksheets are written such that students can work through them in their own time and at their own pace outside of the timetabled session, which is then used for troubleshooting and discussion of ideas. Collaborative workshops make use of the lecture and lab material with students undertaking and discussing quantitative analyses of case studies from the natural sciences. The workshop activities and roles are structured in such a way as to reinforce the collaborative and investigative nature of the scientific method.
A diagnostic quiz and student attitudes survey is released pre-semester to provide students with information about how their skills compare to the assumed knowledge and to reflect on their engagement with quantitative methods in the past, present and future. The student attitudes survey is taken again at the end of the semester to give students a chance to reflect on their experiences within the unit.

Assessment items

Academic integrity

QUT is committed to maintaining high academic standards to protect the value of its qualifications. To assist you in assuring the academic integrity of your assessment you are encouraged to make use of the support materials and services available to help you consider and check your assessment items. Important information about the university's approach to academic integrity of assessment is on your unit Blackboard site.

A breach of academic integrity is regarded as Student Misconduct and can lead to the imposition of penalties.

Resource materials

There are no required textbooks for SEB113. A list of recommended and additional resources will be provided via QUT Readings.
The following books are recommended as references during the semester. You do not need to purchase these books, as they are available at no charge to students as eBooks through the QUT Library or the authors' website:
· Faraway, J. J. Linear Models with R. Chapman and Hall/CRC, 2016.
· Wickham, H. & Grolemund, G. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O'Reilly Media, 2017
· Strang, G. Calculus. Wellesley-Cambridge Press, 1991.
The following book is recommended to those students wishing to have a general overview of the use of statistics in modern scientific research, with case studies from a range of natural sciences:
· Diggle, P. and Chetwynd, A. Statistics and Scientific Method: an introduction for students and researchers. Oxford University Press, 2011.
All computation will be performed with the R software inside the RStudio integrated development environment. Both of these pieces of software are required for performing analyses, are available in QUT's SEF computer labs and are available online at no charge for students to install on to their personal computers.

Risk assessment statement

There are no out of the ordinary risks associated with this unit. You will be made aware of evacuation procedures and assembly areas in the first few lectures. In the event of a fire alarm sounding, or on a lecturer's instruction, you should leave the room and assemble in the designated area which will be indicated to you. You should be conscious of your health and safety at all times whilst on campus or in the field.