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Unit Summary

Unit type

UG Coursework Unit

Credit points

12

AQF level

7

Level of learning

Introductory

Unit aim

Introduces statistical methods required for environmental science/management; the different types of variables, exploring data with descriptive statistics, graphically presenting data, performing tests of significance (chi-square, t-test, correlation, regression and analysis of variance) and presenting the results of statistical analyses. Emphasis is placed on matching suitable data with an appropriate statistical method in an environmental management setting and developing a "tool kit" of skills and resources to help students become independent in data management and analysis.

Unit content

  • Data management skills and descriptive statistics with Microsoft Excel, scientific calculators and SPSS, including; variable types, measurements and units, number skills, rounding, significant figures, preparing data for statistical analysis, graphs and data transformation 
  • Measures of central tendency (mean, mode and median) and dispersion (standard error, variance and standard deviation)
  • Dealing with uncertainty
    • Populations and samples
    • Probability distributions
    • The normal distribution
    • Confidence intervals
    • Type I and Type II error
  • Hypotheses testing for differences
    • Student's t test
    • Analysis of variance
  • Hypotheses testing for relationships/association
    • Correlation
    • Linear regression
  • An introduction to non-parametric equivalents of common tests
  • Hypothesis testing with categorical data: Chi square
  • Presenting different variable types and the results of hypothesis testing in a professional manner
  • Experimental and survey design

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

GA1: Intellectual rigour, GA2: Creativity, GA3: Ethical practice, GA4: Knowledge of a discipline, GA5: Lifelong learning, GA6: Communication and social skills, GA7: Cultural competence
On completion of this unit, students should be able to: GA1 GA2 GA3 GA4 GA5 GA6 GA7
1 show recognition of the different types of variables used in environmental science/management (nominal, ordinal, discrete and continuous) Knowledge of a discipline
2 calculate means, standard deviations, variance and chi square, using a scientific calculator Knowledge of a discipline
3 propose a suitable research question, develop methodologies that would lead to collection of the correct type of data and perform appropriate statistical tests for an investigation relevant to environmental science/management Intellectual rigour Knowledge of a discipline Lifelong learning
4 state the null hypothesis, calculate required values and interpret the following statistical tests, chi square, t test, correlation, regression and analysis of variance for research questions relevant to environmental science/management Intellectual rigour Knowledge of a discipline
5 explain the difference between a population and a sample and have a basic understanding of key concepts, symbols and terms relevant to survey and experimental design Knowledge of a discipline
6 interpret the results of statistical tests and explain the consequences of Type I and Type II errors in tests of significance and explain the consequences of Type I and Type II errors to environmental management Intellectual rigour Knowledge of a discipline Lifelong learning
7 interpret statistical tests of significance in environmental management problems. Intellectual rigour Knowledge of a discipline Lifelong learning

On completion of this unit, students should be able to:

  1. show recognition of the different types of variables used in environmental science/management (nominal, ordinal, discrete and continuous)
    • GA4: Knowledge of a discipline
  2. calculate means, standard deviations, variance and chi square, using a scientific calculator
    • GA4: Knowledge of a discipline
  3. propose a suitable research question, develop methodologies that would lead to collection of the correct type of data and perform appropriate statistical tests for an investigation relevant to environmental science/management
    • GA1: Intellectual rigour
    • GA4: Knowledge of a discipline
    • GA5: Lifelong learning
  4. state the null hypothesis, calculate required values and interpret the following statistical tests, chi square, t test, correlation, regression and analysis of variance for research questions relevant to environmental science/management
    • GA1: Intellectual rigour
    • GA4: Knowledge of a discipline
  5. explain the difference between a population and a sample and have a basic understanding of key concepts, symbols and terms relevant to survey and experimental design
    • GA4: Knowledge of a discipline
  6. interpret the results of statistical tests and explain the consequences of Type I and Type II errors in tests of significance and explain the consequences of Type I and Type II errors to environmental management
    • GA1: Intellectual rigour
    • GA4: Knowledge of a discipline
    • GA5: Lifelong learning
  7. interpret statistical tests of significance in environmental management problems.
    • GA1: Intellectual rigour
    • GA4: Knowledge of a discipline
    • GA5: Lifelong learning

Prescribed texts

  • No prescribed texts.
Prescribed texts may change in future study periods.