Download Applied Statistics Using SPSS, STATISTICA and MATLAB by Joaquim P. Marques de Sá PDF

By Joaquim P. Marques de Sá

ISBN-10: 3662058049

ISBN-13: 9783662058046

ISBN-10: 3662058065

ISBN-13: 9783662058060

Intended for an individual wanting to use statistical research to a wide number of technology and engineering difficulties, this booklet exhibits tips to use SPSS, MATLAB, STATISTICA and R for information description, statistical inference, type and regression, issue research, survival information and directional data. The second version contains the R language, a brand new part on bootstrap estimation tools and a more robust therapy of tree classifiers, plus extra examples and exercises.

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STATISTICA, SPSS and MATLAB commands used to obtain box lots. , indices that are useful for the purpose of summarising the data. These indices are known as descriptive statistics. All descriptive statistics prsented in the following sections are accessible through the Descriptive Statistics commands ofthe STATISTICA, SPSS and MATLAB. 7. STATISTICA, SPSS and MATLAB commands used to obtain descriptive statistics. 1 Measures of Location Measures of location are used in order to determine where the data distribution is concentrated.

I0 I Introduction Several stat1sttcs, whose only assumption is the existence of a total order relation, can be applied to ordinal data. 2. Continuous variables have a real number interval (or a reunion of intervals) as domain, which is unique up to a linear transformation. One can further distinguish between ratio type variables, supporting linear transformations of they = ax type, and interval type variables supporting linear transformations of they= ax+ b type. The domain of ratio type variables has a fixed zero.

STATISTICA, SPSS and MATLAB commands used to obtain cross tables. STATISTICA Statistics; Basic Statistics and Tables; Descriptive Statistics; (Tables and banners I Multiple Response Tables) SPSS Analyze; Descriptive Statistics; Crosstabs MATLAB cross tab (x, y) • 42 2 Presenting and Summarising the Data The most popular graphical tools for multivariate data are the scatter plots for bivariate data and the 3D plots for trivariate data . 20. 20); therefore, in normal practice, one often inspects multivariate data graphically through scatter plots of the variables grouped in pairs.

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