Shows how various categories of flow-cytometry data can be analysed to produce useful information.This book covers the means by which large quantities of data from flow cytometers can be converted into usable information, mainly by basic number handling concepts, regression analysis, probability functions, statistical tests, and methods of analysing dynamic processes.This book covers the means by which large quantities of data from flow cytometers can be converted into usable information, mainly by basic number handling concepts, regression analysis, probability functions, statistical tests, and methods of analysing dynamic processes.This book covers very basic number handling techniques, regression analysis, probability functions, statistical tests and methods of analyzing dynamic processes from flow cytometry data. These are developed for the analysis of not only individual DNA histograms to obtain the proportion of cells in the cell cycle phases, but also time courses of DNA histograms to yield cell cycle kinetic information; overlapping immunofluorescence distributions with confidence limits for the estimated proportions; enzyme kinetic and membrane transport parameters and a brief introduction to multivariate analysis is given. A distinction is made between data handling, for example gating and counting the numbers of cells within that gate, a process commonly regarded as data analysis but which, in reality, is data handling, and data analysis itself which is the means by which information is extracted.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. Multi-variant analysis primer; 12. Epilogue; Appendices; References; Index. I recommend this book as an introduction to statistics for the mathematically intimidated and as a gatls>