Unit rationale, description and aim
Statistics informs many aspects of contemporary society through applications in business, education, science and the household and at all levels; globally, locally, socially and economically. As a result, some level of statistical literacy is essential in science and social science disciplines.
This unit provides an introduction to descriptive statistics, probability, random variables and their use in inferential statistics. Discrete and continuous distributions will be considered with a focus on the normal distribution. The unit will also consider sampling distributions and the examination of estimation and hypothesis testing including analysis of variance. Bivariate data analysis using regression and correlation will also be introduced. Appropriate technology for statistical analysis will be used including computer packages such as Microsoft Excel and R. The importance of correct and ethical use of statistics will be discussed.
The aim of this unit is to provide students with a reasonably sophisticated understanding of statistics, the ability to understand statistical statements and to judge the appropriateness of any chosen statistical test.
Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
Analyse and critically evaluate data sets using ap...
Learning Outcome 01
Use basic techniques of probability and probabilit...
Learning Outcome 02
Communicate statistical knowledge to others, and u...
Learning Outcome 03
Content
Topics will include:
- Introduction to Statistics and statistical software
- Introduction to Data analysis
- Introduction to probability and combinatorics
- Random variables and probability distributions
- Discrete probability distributions including binomial, Poisson and discrete uniform
- Continuous distributions including normal, exponential and continuous uniform
- Hypothesis testing and confidence intervals
- Student t-distribution, Chi-squared distribution, and F-distribution
- ANOVA (Analysis of Variance)
- Correlation and regression
Assessment strategy and rationale
To successfully complete an undergraduate Mathematics sequence, students need an understanding of a variety of basic Mathematical topics and an ability to apply that understanding to a variety of problems. To succeed at problem solving in Mathematics, students must have these skills at their fingertips and be able to recall them and choose an appropriate approach under some pressure. The assessment strategy chosen, while traditional, tests and supports student learning by providing opportunities to develop and test their problem-solving skills through the unit.
At specified times, through the semester, students will sit two supervised components to ensure that students have fully integrated the learning and can bring a variety of strategies to solve a variety of problems. The take home assignment will allow students to develop other skills including traditional and technological problem-solving methods.
Overview of assessments
Assessment Task 1: Take Home Assignment(s) Contin...
Assessment Task 1: Take Home Assignment(s)
Continuous assessment – A single task which is submitted in 1, 2 or 3 parts across the semester as stipulated by the lecturer.
30%
Assessment Task 2: Test Content and application t...
Assessment Task 2: Test
Content and application test 1. This test will be conducted under supervision and on campus.
35%
Assessment Task 3: Test Content and application ...
Assessment Task 3: Test
Content and application test 2. This test will be conducted under supervision and on campus.
35%
Learning and teaching strategy and rationale
As is common in Mathematics a variety of Active Learning approaches promote the best acquisition of skills and understanding. Lectures will typically be structured to provide explanations of the material to be covered, along with examples of the applications of that material, as well as formal and informal tasks for students that will reinforce that learning. Splitting the taught content of the lectures into short topics will ensure increased student engagement with the material, as well as providing opportunities for students to consolidate their learning before new material is covered.
This allows students to learn the skills and then build understanding, competence and confidence through face-to-face tutorials that ideally occur face to face. Face-to-face learning supports immediate feedback, peer interaction, and collaborative problem-solving (essential elements in developing mathematical thinking) while also enabling tutors to identify and address misconceptions early.
Continuous formative learning opportunities allow for the early detection of problems a student might be having and ensures that appropriate guidance can be given early enough to support later learning in the unit. Students will be expected to submit written responses to questions involving core mathematical concepts, methods, and problem-solving strategies. In all cases this should be supported using available online technology.