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Unit of Study MAT00211 - Environmental Information Analysis (2018)

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Learning outcomes and graduate attributes

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.

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

GA1: Intellectual rigour, GA2: Creativity, GA3: Ethical practice, GA4: Knowledge of a discipline, GA5: Lifelong learning, GA6: Communication and social skills, GA7: Cultural competence
Learning outcome count Learning outcome description GA1 GA2 GA3 GA4 GA5 GA6 GA7
1 develop scientific questions to direct design and analysis selection
2 show recognition of the different types of variables used in environmental science/management, calculate means, modes, medians, standard deviations, standard error, variance, confidence intervals and chi square, using a scientific calculator and Microsoft Excel
3 state the null hypothesis, prepare data for statistical analysis, calculate required values and interpret the results of the following statistical tests, chi square, t test, correlation, regression and analysis of variance for research questions relevant to environmental science/management
4 present the results of statistical tests of significance in a professional manner, including using Microsoft Excel or SPSS to produce high quality graphs (appropriate to the type of variables presented)
5 explain the consequences of Type I and Type II errors in tests of significance in context of environmental science/management and demonstrate a basic understanding of the validation of a chosen statistical method
6 propose a suitable research question, develop methodologies that would lead to collection of the correct type of data and choose appropriate statistical tests for an investigation relevant to environmental science/management
7 explain the difference between a population and a sample and demonstrate a basic understanding of key concepts, symbols and terms relevant to survey and experimental design.

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

  1. develop scientific questions to direct design and analysis selection
    • GA1:
    • GA4:
    • GA5:
  2. show recognition of the different types of variables used in environmental science/management, calculate means, modes, medians, standard deviations, standard error, variance, confidence intervals and chi square, using a scientific calculator and Microsoft Excel
    • GA4:
  3. state the null hypothesis, prepare data for statistical analysis, calculate required values and interpret the results of the following statistical tests, chi square, t test, correlation, regression and analysis of variance for research questions relevant to environmental science/management
    • GA1:
    • GA4:
  4. present the results of statistical tests of significance in a professional manner, including using Microsoft Excel or SPSS to produce high quality graphs (appropriate to the type of variables presented)
    • GA1:
    • GA4:
    • GA5:
  5. explain the consequences of Type I and Type II errors in tests of significance in context of environmental science/management and demonstrate a basic understanding of the validation of a chosen statistical method
    • GA1:
    • GA4:
    • GA5:
  6. propose a suitable research question, develop methodologies that would lead to collection of the correct type of data and choose appropriate statistical tests for an investigation relevant to environmental science/management
    • GA1:
    • GA4:
    • GA5:
  7. explain the difference between a population and a sample and demonstrate a basic understanding of key concepts, symbols and terms relevant to survey and experimental design.
    • GA1:
    • GA4:

Prescribed learning resources

Prescribed Texts
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Prescribed Learning Resources may change in future Teaching Periods.