Statistical Modelling in Higher Learning - Mamvura, Innocent
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Statistical Modelling in Higher Learning:The book explains the factors that predict the time taken to complete degree programmes.The book presents you with a solid understanding on the predictors using classification tree mining and logistic regression analysis.Classification is the process of forming groups from a large set of cases based on their characteristics.The Classification Tree procedure creates a Tree-based Classification Model which predicts values of the outcome variable based on values of independent variables.Binary Logistic Regression is a technique used when the outcome…mehr

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Produktbeschreibung
Statistical Modelling in Higher Learning:The book explains the factors that predict the time taken to complete degree programmes.The book presents you with a solid understanding on the predictors using classification tree mining and logistic regression analysis.Classification is the process of forming groups from a large set of cases based on their characteristics.The Classification Tree procedure creates a Tree-based Classification Model which predicts values of the outcome variable based on values of independent variables.Binary Logistic Regression is a technique used when the outcome variable is a dichotomous variable (has two values). Logistic Regression uses Binomial Probability Theory in which there are only two outcome categories. The technique forms a function using the Maximum Likelihood Method, which maximizes the chances of grouping the observed data into the suitable category given the regression coefficients
Autorenporträt
Innocent the author ,is a PhD Student,and is doing some work on Data Streams Mining:Big Velocity Data.His research interests are on educational data mining,mining data streams,big data,multivariate data analysis,statistical modelling and business intelligence.