This slim volume provides a very approachable guide to the techniques and basic ideas of probability and statistics and more advanced techniques such as generalised linear models, classification using logistic regression, and support-vector machines.
This slim volume provides a very approachable guide to the techniques and basic ideas of probability and statistics and more advanced techniques such as generalised linear models, classification using logistic regression, and support-vector machines.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr Upton studied at Leicester and Birmingham Universities before taking up a position at the University of Newcastle-upon Tyne. From 1973 until 2014 he taught at the University of Essex, where his responsibilities included time as a dean and as a head of department. His varied data analysis included making sense of British voting figures, identifying gene patterns using microarrays, and estimating rainfall using many different measuring instruments. Dr Brawn is the holder of two PhDs: in Seismology from the University of Witwatersrand (1989); in Applied Statistics from the University of Essex (2009), both fields involving considerable data analysis. His extensive teaching experience covers many branches of the mathematical sciences and has most recently focused on introducing data analysis to students with limited mathematical background.
Inhaltsangabe
1.: First steps 2.: Summarising data 3.: Probablity 4.: Probability distributions 5.: Estimation and confidence 6.: Models, p-values, and hypotheses 7.: Comparing proportions 8.: Relations between two continous variable 9.: Several explanatory variables 10.: Classification 11.: Last Words
1.: First steps 2.: Summarising data 3.: Probablity 4.: Probability distributions 5.: Estimation and confidence 6.: Models, p-values, and hypotheses 7.: Comparing proportions 8.: Relations between two continous variable 9.: Several explanatory variables 10.: Classification 11.: Last Words
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