ASC214 Applied Statistics and Animal Epidemiology (8)

This subject provides an introduction to the fundamental research and analytical skills required to answer questions posed by practitioners and scientists within the equine and veterinary technology industries. Students will examine the principles of experimental design which ensure that research conducted is well planned and able to provide useful and reliable results. Students will develop expertise in the correct formulation of hypotheses that are fundamental to statistical testing along with the requirements for data collection, collation and preparation for analysis. A range of appropriate descriptive and analytical statistical methods will be covered, along with an introduction to quantitative animal-based epidemiology to assess and analyse problems in animal populations. On successful completion of this subject, students should be able to develop a well-designed study, apply appropriate statistical analysis and appraise the conclusions with respect to the statistical outcomes for a range of industry-based problems.

Availability

Session 2 (60)
On Campus
Wagga Wagga Campus
Online
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: ASC214. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Animal and Veterinary Sciences

Enrolment Restrictions

Students enrolled in the Bachelor of Equine Science (with specialisation) or Bachelor of Veterinary Technology.
Other students with permission of their Course Director and the Subject Coordinator.
Not available to students who have successfully completed ASC114. 

Assumed Knowledge

Basic numeracy skills.

Subject Relationships

ASC114 ASC214 replaces ASC114

Incompatible Subjects

ASC114

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to explain the research cycle and plan research studies;
  • be able to design research studies in order to generate usable data;
  • be able to identify appropriate data collection, collation (management) and analysis methods and apply these in order to test hypotheses and reach statistically valid conclusions about research questions;
  • be able to use statistical software to conduct simple descriptive and analytical statistics of industry related data;
  • be able to apply basic epidemiological concepts to the assessment of contemporary problems within the animal industries;
  • be able to apply appropriate interpretation and inference skills based on the hierarchy of evidence for epidemiological investigations; and
  • be able to reach informed statistical-based conclusions and communicate these appropriately to a range of audiences.

Syllabus

This subject will cover the following topics:
  • Research Planning - research cycle, principles of experimental design, randomisation, replication, error, sample sizes, subject selection and sampling strategies. Other external considerations e.g. ethics, economics, seasonality.
  • Research Planning - research questions, aims, objectives and hypotheses.
  • Data Organisation - data collection, collation and management.
  • Dealing with Data - data distributions, testing for normality, parametric versus non-parametric testing, transforming data.
  • The Statistical Method - hypothesses probability, significance and the critical umber (P<0.05)
  • Descriptive Statistics - measures of central tendency (averages, mean, median, mode) and variation (variance, standard deviation, standard error of the mean, range and interquartile range), percentages and proportions.
  • Analytical Statistics - differences (t tests and simple analysis of variance), relationships (correlation and simple linear regression) and associations (Chi-squared).
  • Epidemiological methods - observational versus intervention, population versus individual, descriptive versus analytical, prevalence studies versus case control studies versus cohort (follow-up studies). Risk factors and the importance of frequency, dynamics and associations; interpretation and inference skills based on the hierarchy of evidence.
  • Communication skills - basic principles of communication, pitching content at the right level.

The information contained in the CSU Handbook was accurate at the date of publication: June 2022. The University reserves the right to vary the information at any time without notice.

Back