parametric nonparametric data analysis de gunarto hary (4 résultats)

Taschenbuch. Etat : Neu. Neuware -¿Parametric & Non-parametric Data Analysis for Social Research : IBM SPSS¿ offers students in business and social sciences an introduction to basic statistics. It presents how data analysis and statistical processing provide information & solutions to some practical problems. With many cases and exercises in each chapter, this text is easy to understand on common statistical methods to create data summary, report & interpretations using IBM SPSS software. This text consists of 7 comprehensive chapters on parametric and non-parametric statistics and covers nominal, ordinal and continuous data, descriptive statistics, histogram, graphs/plot/charts, parametric/ normality test and level of significance. The text also discusses hypothesis testing for dependent and independent samples and analysis of variance. The author also discusses on correlation among variables and relationship between two numeric variables (simple and logistic regression) as well as potentially nonlinear relationships among more than two independent variables (multiple regression). The last 2 chapters introduce time-series and factor analysis which can be applied to most common data in business & social research.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch.

Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gunarto HaryHary Gunarto received B.Sc. degree in physics from University of Gadjah Mada, and M.Sc. degree from University of Wisconsin, Madison and Ph.D. degree in Electrical and Computer Engineering from Washington State Universit.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Parametric & Non-parametric Data Analysis for Social Research : IBM SPSS' offers students in business and social sciences an introduction to basic statistics. It presents how data analysis and statistical processing provide information & solutions to some practical problems. With many cases and exercises in each chapter, this text is easy to understand on common statistical methods to create data summary, report & interpretations using IBM SPSS software. This text consists of 7 comprehensive chapters on parametric and non-parametric statistics and covers nominal, ordinal and continuous data, descriptive statistics, histogram, graphs/plot/charts, parametric/ normality test and level of significance. The text also discusses hypothesis testing for dependent and independent samples and analysis of variance. The author also discusses on correlation among variables and relationship between two numeric variables (simple and logistic regression) as well as potentially nonlinear relationships among more than two independent variables (multiple regression). The last 2 chapters introduce time-series and factor analysis which can be applied to most common data in business & social research. 156 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Parametric & Non-parametric Data Analysis for Social Research : IBM SPSS' offers students in business and social sciences an introduction to basic statistics. It presents how data analysis and statistical processing provide information & solutions to some practical problems. With many cases and exercises in each chapter, this text is easy to understand on common statistical methods to create data summary, report & interpretations using IBM SPSS software. This text consists of 7 comprehensive chapters on parametric and non-parametric statistics and covers nominal, ordinal and continuous data, descriptive statistics, histogram, graphs/plot/charts, parametric/ normality test and level of significance. The text also discusses hypothesis testing for dependent and independent samples and analysis of variance. The author also discusses on correlation among variables and relationship between two numeric variables (simple and logistic regression) as well as potentially nonlinear relationships among more than two independent variables (multiple regression). The last 2 chapters introduce time-series and factor analysis which can be applied to most common data in business & social research.