Book contents
- Frontmatter
- Contents
- Introduction
- How important is maths in data-handling?
- Abbreviations and the Système International
- Acknowledgements
- 1 Numbers and indices
- 2 A sense of proportion
- 3 Graphs
- 4 Algebra
- 5 Logarithms: exponential and logarithmic functions
- 6 Simple statistics
- 7 Preparing solutions and media
- 8 Enzymes
- 9 Spectrophotometry
- 10 Energy metabolism
- 11 Radioactivity
- 12 Growth in batch cultures
- 13 Growth in continuous culture
- 14 Microbial genetics
- 15 Problems
- 16 Advice and hints
- 17 Answers to problems
- Conclusion
- Further reading
- Index
How important is maths in data-handling?
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Introduction
- How important is maths in data-handling?
- Abbreviations and the Système International
- Acknowledgements
- 1 Numbers and indices
- 2 A sense of proportion
- 3 Graphs
- 4 Algebra
- 5 Logarithms: exponential and logarithmic functions
- 6 Simple statistics
- 7 Preparing solutions and media
- 8 Enzymes
- 9 Spectrophotometry
- 10 Energy metabolism
- 11 Radioactivity
- 12 Growth in batch cultures
- 13 Growth in continuous culture
- 14 Microbial genetics
- 15 Problems
- 16 Advice and hints
- 17 Answers to problems
- Conclusion
- Further reading
- Index
Summary
The answer is vitally, but do not despair. There are few areas of microbiology or biochemistry that require any kind of advanced mathematical ability. What is necessary is to know how to crank out answers from standard methods. Most students, and most of their teachers too, have not been trained to a high level in mathematics. In the author's case this means trained only as far as School Certificate, the forerunner of ‘O’ level. An expert is usually consulted in those rare cases where advanced knowledge is needed.
Students are expected to be numerate, and modest skills are certainly necessary. Appreciation of simple proportion, knowledge of some easy algebra (such as solving simultaneous equations), an understanding of logarithms and basic statistics, and the ability to draw and interpret graphs are all needed. These topics are revised in the first chapters of this book. However, most important of all is to develop a confidence that nearly all data-handling problems can be tackled without having to be a talented mathematician.
Clear thinking and simple mathematics will solve most problems (at least in this branch of science)
The fact is that there are few more ‘popular’ subjects than mathematics. Most people have some appreciation of mathematics, just as most people can enjoy a pleasant tune, and there are probably more people really interested in mathematics than in music. […]
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- Information
- Data-Handling in Biomedical Science , pp. xiPublisher: Cambridge University PressPrint publication year: 2010