Miriam Diamond, Department of Geography, The University of Toronto, Ontario, Canada
George Arhonditsis, Department of Physical and Environmental Sciences, The University of Toronto, Ontario, Canada
Student Projects in Environmental Science provides an accessible introduction to the key stages involved when undertaking a research project. Beginning with a discussion of what constitutes research, the book shows how to develop and plan a feasible research topic based upon a testable hypothesis. It then stresses the importance of logical experimental design that facilitates the use of appropriate statistical treatment of data so that the research questions posed may be answered.
To reinforce key points, use is made throughout of illustrative case studies covering a wide range of topics. The book develops student understanding of what statistical tests are appropriate to use when analyzing their data, and offers practical guidance on how these may be conducted using widely used commercially available software such as Excel, Minitab, and SPSS.
An invaluable text for undergraduates and Masters level students taking courses in Environmental Science and Physical Geography.
- The only text to cover generic project issues such as research planning/resource management and specialist environmental science material in one book.
- Takes a case–study approach to illustrate the range of environmental science topics that students may encounter with cases supplied by specialists in the field.
- Practical worked examples and self–assessment tasks illustrate key statistical and mathematical points so as to keep heavy theory to a minimum.
1. General strategies for completing your research project successfully.
1.1 Introduction why is this book necessary?
1.2 What on earth am I going to do for my research project?
1.3 Fundamentals of scientific research, the generation and testing of hypotheses (see also Chapter 3).
1.4 What constitutes research? Distinguishing between monitoring and research
1.5 Project planning
1.6 Conducting your project safely
1.7 How to conduct a literature review (see also chapter 7)
1.8 How to be a research student
1.9 How to manage your supervisor
2. Gathering your data.
2.1 Different types of data
2.2 Designing an experimental research project
2.3 How reliable are your data?
3. How to summarise your data.
3.1 Descriptive statistics
3.2 Probabilities and data distributions
3.3 Choosing the appropriate statistical test
4. Testing hypotheses.
4.1 Coincidence or causality?
4.2 Relationships and differences
4.3 Testing for differences
5. Spotting relationships.
5.1 Linear regression to what extent does one factor influence another?
5.2 Multiple linear regression to what extent is a given variable influenced by a range of other variables?
5.3 Non–linear regression
5.4 Pattern recognition
6. Making sense of past, present and future systems mathematical modelling.
6.1 What is a model?
6.2 Functions of models
6.3 Which type of model should I use?
6.4 How do I build a model?
6.5 Steps in developing a model
6.6 Illustrative case study
7. Presenting your work.
7.1 Getting started strategies for successful writing
7.2 How to write your dissertation
7.3 How to represent graphically your data
7.4 How to cite references
7.5 How to defend your work in an oral exam
7.6 How to make effective oral presentations