Description

Book Synopsis
A one-stop resource for quantitative environmental science methodology, this guide walks readers through their research project from the initial stages of choosing a suitable topic, conducting the relevant experiments, and interpreting the data through an effective presentation of the results.

Table of Contents
Preface

Acknowledgement

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

1.10 Summary

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

7.7 Summary

Index

Student Projects in Environmental Science

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    RRP £32.95 – you save £1.65 (5%)

    Order before 4pm today for delivery by Mon 6 Jul 2026.

    A Paperback / softback by Stuart Harrad, Lesley Batty, Miriam Diamond

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      View other formats and editions of Student Projects in Environmental Science by Stuart Harrad

      Publisher: John Wiley & Sons Inc
      Publication Date: 09/05/2008
      ISBN13: 9780470845660, 978-0470845660
      ISBN10: 047084566X

      Description

      Book Synopsis
      A one-stop resource for quantitative environmental science methodology, this guide walks readers through their research project from the initial stages of choosing a suitable topic, conducting the relevant experiments, and interpreting the data through an effective presentation of the results.

      Table of Contents
      Preface

      Acknowledgement

      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

      1.10 Summary

      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

      7.7 Summary

      Index

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