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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  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:

develop scientific questions to direct design and analysis selection
 GA1:
 GA4:
 GA5:

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:

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:

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:

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:

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:

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 texts
 All students will need a print copy of this textbook. This textbook provides the scaffolding around which we will build the toolkit of skills you will require to complete all assessment items and for the remainder of your degree: Ennos, R & Johnson, M, 2018, Statistical and Data Handling Skills in Biology, 4th edn, Pearson United Kingdom, Harlow, England. ISBN: 9781292086033.