STAT5005 Quantitative Biology Assessment

Syllabus

An introduction to a variety of statistical procedures which are frequently used in the biological sciences. Populations and samples, types of data, distributions, measures of central tendency and dispersion, graphing techniques, data screening, data transformation, diversity indices, one-way ANOVA, two-way ANOVA, post-hoc testing, dependent, independent and one-sample t-tests, simple linear regression and correlation, non-parametric procedures (Mann-Whitney U test, Kruskal Wallis, Spearman Rank Correlation, Chi-square and contingency tables), over-view of multivariate ecological techniques. Experimental design, interpretation of analyses and report writing. Data analysis using the statistical package SPSS.

Introduction

Welcome to Quantitative Biology,

This unit is designed to provide students with the knowledge and skills that are necessary to design successful experiments and subsequently to summarise, analyse, interpret and present data in a format appropriate for research reports, dissertations or papers. The knowledge and skills from this unit are critical for project work and for the successful completion of other units at second and third year level in the Bachelor of Science. We will be using the statistical package RStudio during the computer laboratory sessions. This free and powerful statistical software package provides a robust, reproducible and transparent approach for data analysis. All students in this unit will attend a weekly in-person lecture, which will also be available as an iLecture. We will also hold a weekly in-person workshop and a face to face computer laboratory class every week. It’s important to note that in addition to the weekly face to face classes, all students have the opportunity to contact me for additional consultation. I am available for both virtual and face to face consult. Please email me to make an appointment.

Unit Learning Outcomes
All graduates of Curtin University achieve a set of six Graduate Capabilities during their course of study. These
inform an employer that, through your studies, you have acquired discipline knowledge and a range of other skills
and capabilities which employers would value in a professional setting. Each unit in your course addresses the
Graduate Capabilities through a clearly identified set of learning outcomes. They form a vital part in the process
referred to as assurance of learning. The learning outcomes notify you of what you are expected to know,
understand or be able to do in order to be successful in this unit. Each assessment for this unit is carefully
designed to test your knowledge of one or more of the unit learning outcomes. On successfully completing all of
the assessments you will have achieved all of these learning outcomes.
Your course has been designed so that on graduating you will have achieved all of Curtin's Graduate Capabilities
through the assurance of learning processes in each unit.

Learning Activities
This unit will be delivered via a combination of in-person Lectures, workshops and computer laboratory sessions.
It is in your own interest to attend all classes and fully utilise the two-hour laboratory session; the outcomes of this
unit cannot be achieved without this attendance. A lot more happens in the lectures and workshops than the
delivery of content! The lectures and workshops will involve exercises, discussion, activities, quizzes and
demonstrations. The lectures will also be a vital source of feedback for you in many ways. For this reason, online
material, lecture notes or the text alone cannot substitute for attendance during class time. The competent use of
Excel and RStudio will rely on skills and guided practice gained during the laboratory sessions.

Detailed information on assessment tasks

• The data analysis assessment will focus on your understanding of simple statistical analysis. In the week 2
  computer lab class the assignment will be introduced. The assessment will ask you to demonstrate your
  understanding of a piece of statistical code by providing annotations, choose appropriate data analysis,
  and write up the methods and results of statistical analysis using appropriate scientific writing. The
  assessment must be submitted through Turnitin. A detailed marking rubric and assessment outline will be
  provided.
• This assessment will develop on your understanding of experimental design and statistical
  analysis. You will design an experiment, collect data, and provide a well-considered written
  data interpretation section and valid conclusions. The final output will be in the form of a
  scientific paper. The assessment must be submitted through Turnitin. You will be provided with
  a detailed rubric during semester.
• The exam will assess material covered in all lectures, workshops AND laboratories. The exam
  focuses on selecting the appropriate statistical analysis, justification of this choice, and the
  interpretation of statistical output. You are not required to run any analysis.

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