Book contents
- Frontmatter
- Contents
- 1 Introduction
- 2 Fundamental concepts
- 3 Probability functions
- 4 Significance testing and fit criteria
- 5 Regression analysis
- 6 Flow cytometric sources of variation
- 7 Immunofluorescence data
- 8 DNA histogram analysis
- 9 Cell-cycle kinetics
- 10 Dynamic cellular events
- 11 Multivariate analysis primer
- 12 Epilogue
- Appendix 1: Numerical integrating routine
- Appendix 2: Normal distribution probabilities
- Appendix 3: Variance ratio tables
- Appendix 4: Mann-Whitney U tables
- Appendix 5
- Appendix 6: Regression analysis for y on x
- Appendix 7
- Appendix 8
- Appendix 9
- References
- Index
2 - Fundamental concepts
Published online by Cambridge University Press: 27 October 2009
- Frontmatter
- Contents
- 1 Introduction
- 2 Fundamental concepts
- 3 Probability functions
- 4 Significance testing and fit criteria
- 5 Regression analysis
- 6 Flow cytometric sources of variation
- 7 Immunofluorescence data
- 8 DNA histogram analysis
- 9 Cell-cycle kinetics
- 10 Dynamic cellular events
- 11 Multivariate analysis primer
- 12 Epilogue
- Appendix 1: Numerical integrating routine
- Appendix 2: Normal distribution probabilities
- Appendix 3: Variance ratio tables
- Appendix 4: Mann-Whitney U tables
- Appendix 5
- Appendix 6: Regression analysis for y on x
- Appendix 7
- Appendix 8
- Appendix 9
- References
- Index
Summary
Handling and interpreting numbers is not generally a “strong point” for biologists. This applies particularly when there is a large group of numbers that are more easily handled and understood by using some average value as a summary. Indeed, large groups of numbers must be handled by some sort of summary system, because just supplying the raw data – say, 10,000 fluorescence or light-scatter recordings from a flow cytometric analysis run – would be essentially unintelligible. This chapter was included to re-familiarise the reader with some very basic number handling concepts and to set the scene for converting numbers into information.
Central tendency
If we make a number of measurements on a population, say the weights, shapes and various dimensions of 1000 females between the ages of 15 and 25, we will end up with a large series of numbers. I have chosen this particular example not because I'm a male chauvinist pig, but because I was recently talking with a designer of female undergarments who had the task of converting those numbers into articles for sale on the shelves of a large retail outlet. The end points of the survey were to make the articles as appealing as possible (that was the first consideration), in the minimum number of different shapes and sizes as possible, as cheaply as possible, and to sell all of them all the time.
- Type
- Chapter
- Information
- Flow Cytometry Data AnalysisBasic Concepts and Statistics, pp. 4 - 19Publisher: Cambridge University PressPrint publication year: 1992
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