Overview

This unit of study enables students to develop the capacity to undertake independent statistical investigations, including the assumptions and limitations of their application. The unit will provide practical skills to allow students to meaningfully interpret the results of various hypothesis tests, as well as to understand probability distributions and sampling methods commonly applied when collecting data.

Requisites

Equivalent units
FIN10002 Financial Statistics
STA60001 Statistical Practice 1
Other equivalents
  • HAYG411 - Statistics and Research Methods; 
  • HMA103 - Statistics and Research Methods; 
  • HMS102 - Introduction to Statistics; LCR102(KS) - Foundations of Statistics; 
  • LCR102Y - Foundations of Statistics; LCR502 - Foundations of Statistics; 
  • LCR102 - Foundations of Statistics; STA10008 - Statistics 101; 
  • STA102(C)(Y) - Foundations of Statistics; 
  • STA15 - Statistics and Research Methods(Software)
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 2
Location
Hawthorn
Start and end dates
29-July-2024
27-October-2024
Last self-enrolment date
11-August-2024
Census date
31-August-2024
Last withdraw without fail date
13-September-2024
Results released date
03-December-2024
Teaching Period 3
Location
Online
Start and end dates
04-November-2024
09-February-2025
Last self-enrolment date
17-November-2024
Census date
29-November-2024
Last withdraw without fail date
27-December-2024
Results released date
04-March-2025

Learning outcomes

Students who successfully complete this unit will be able to:

  • Specify the objectives of an investigation in statistical terms
  • Identify the level of measurement of a variable, appropriate sampling methods, and research design of a study
  • Produce appropriate descriptions and visualisations of data distributions
  • Estimate population parameters (proportions, means) using appropriate statistics and confidence intervals
  • Select and conduct appropriate hypothesis tests for different population parameters (proportions, single sample means, difference of means for matched and independent samples)
  • Describe the relationships between variables (correlations, crosstabs, relative risk and odds ratios) and test the significance of these relationships
  • Interpret the outcomes of data analysis to write a concise report on findings

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Online
Lecture
2.00 12 weeks 24
On-campus
Class
1.00 12 weeks 12
Specified Activities
Various
3.00 12 weeks 36
Unspecified Activities
Various
6.50 12 weeks 78
TOTAL150

All Applicable Locations

Type Hours per week Number of weeks Total (number of hours)
On-campus
Lecture
2.00 12 weeks 24
On-campus
Class
1.00 12 weeks 12
Specified Activities
Various
3.00 12 weeks 36
Unspecified Activities
Various
6.50 12 weeks 78
Live Online
Class
1.00 12 weeks 12
Online
Directed Online Learning and Independent Learning
11.50 12 weeks 138
TOTAL300

Assessment

Type Task Weighting ULO's
AssignmentIndividual 40% 1,3,4,5,6,7 
Online QuizIndividual 20% 2,3,4,5,6,7 
TestIndividual 40% 1,2,6,7 

Content

  • Critical thinking in statistics; confounding and sources of bias
  • Ordering and grouping data: interpretation frequency tables and histograms; summarising data: median, IQR and boxplots; the mean and standard deviation; levels of measurement
  • Describing and displaying relationships; Pearson's; introduction to regression; relationships in tabulated data; correlation and causality
  • Producing data; experiments; population and samples; density curves and normal distribution
  • Introduction to estimation, confidence intervals for proportions, means and correlations
  • Making decisions about means, the Binomial test, t tests; testing relationships; Pearson's r and the Chi-square test of independence.
  • Relative Risk and Odds Ratios
  • Graduate Attribute 2 (Communication 2 - Communicating using different media)
  • Graduate Attribute 5 (Digital Literacies 1 - Information literacy)
  • Graduate Attribute 6 (Digital Literacies 2 - Technical literacy)

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.