Statistics for Forensics
Unit code: HMA280
| Credit points | 12.5 Credit Points |
| Duration | One Semester / Teaching Period |
| Campus | Hawthorn |
| Prerequisites | HMA278 Design and Measurement 2 |
Related course(s)
A unit of study in the Bachelor of Arts, Bachelor of Arts (Psychology and Forensic Science), Bachelor of Social Science and Bachelor of Social Science (Psychology and Forensic Science) programs.
Aims and objectives
Aims:
This subject aims to provide students with the statistical knowledge and skills to support their concurrent and future studies and to teach students advance procedures available in the statistical package PASW for Windows (formerly SPSS for windows). Students will develop the capacity to carry out and report independent statistical investigations, together with an awareness of the assumptions and limitations involved with the generalisation of results of such investigations. In particular this subject guides students through the key statistical techniques used to evaluate various types of forensic evidence. Real-life examples from the forensic science literature and forensic case-work are used to illustrate relevant statistical concepts and methods in areas such as DNA profiling, biochemical matching (e.g. blood stains), probability of re-offence in a given time period, and time to re-offence allowing for data censoring.
After successfully completing this unit, you should be able to:
- Understand basic concepts in probability and the definition of probability as it applies to random events and uncertain evidence.
- Know how to update probabilities when additional information is obtained
- Apply probability to games of chance and forensic science and DNA profiling
- Understand the major uses of binary and multinomial regression
- Use binary regression to predict the probability of success or failure
- Apply and compare different models for a survival analysis, particularly for typical forensic science settings.
- Understand the differences between various clustering methods
- Conduct cluster analyses, particularly in typical forensic science settings
- Apply and compare different classification techniques, particularly in typical forensic science settings.
Teaching methods
Lectures (2 hour), labs (2 hours) and independent study.Forensic science examples will be used to illustrate the usefulness of important statistical methods in this context. This will be done in lectures, computer labs and in all the assessment tasks including the exams.
Assessment tasks will be designed using forensic science data to ensure that students can:‐
- Make a clear statement of the objectives of a study
- Specify and classify the variables of interest in a study according to their level of measurement
- Choose and conduct an appropriate statistical analysis technique using SPSS software
- Use the outcomes of the data analysis to answer the research question
- State the limitations of a study
- Suggest directions for further investigations as a result of a study
- Write a research report
Generic skills outcomes
Key Generic Skills for this Unit of StudyThe graduate attributes which relate to this unit help to produce graduates who :
Are capable in their chosen professional areas
Students will attain statistical knowledge and skills that will support their professional careers. This will include abilities in critical enquiry and report writing, an awareness of the relationship between statistical theory and practice and an appreciation of the strengths and limitations of statistical models.
Are adaptable and manage change
Statistical and research skills are an integral part of studies in the social sciences and other disciplines. Such skills enable students to investigate problems and issues of their own choosing as well as those covered in this subject.
Using appropriate research designs and technology will be an important part of this subject and will assist students to develop a socially responsible awareness of the role of research in society. The development of statistical and research skills will contribute to students being able to critically evaluate the implications of research on economic, social or environmental planning and policy decisions.
Content
Introduction
Crime Statistics
Forensic Statistics
Probability Theory
Crime Statistics
Forensic Statistics
Probability Theory
Analysis of Categorical Data
Crosstabulations
Correspondence Analysis
Loglinear Analysis
Multidimensional Scaling
Classification
Binomial logistic regression
Multinomial logistic regression
Cluster analysis
Survival Analysis
Life Tables
Kaplan-Meier Curves
Cox regressionni
Reading materials
Meyer, D. and Phillips, B. Forensic Statistics (Swinburne Bookstore)
Aitken C.G.G. (2004). Statistics and the Evaluation of Evidence for Forensic Scientists. Chichester: John Wiley & Sons.
Aitken C.G.G. (2004). Statistics and the Evaluation of Evidence for Forensic Scientists. Chichester: John Wiley & Sons.
Lucy, D. (2006). Introductory Statistics for Forensic Scientists. Chichester: John Wiley & Sons.
