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Unit Summary
Unit type
UG Coursework Unit
Credit points
12
AQF level
Level of learning
Introductory
Former School/College
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 (chisquare, ttest, 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 nonparametric 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.
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:
 show recognition of the different types of variables used in environmental science/management
(nominal, ordinal, discrete and continuous)
 GA4: Knowledge of a discipline
 calculate means, standard deviations, variance and chi square, using a scientific
calculator
 GA4: Knowledge of a discipline
 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
 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
 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
 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
 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.