Cross Section Experimental Data by Agung Gusti (26 results)

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Condition: New. pp. xix + 564 Index Standard Edition DISTRIBUTORS PVT. LTD 01149348925.

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Hardcover. Condition: Brand New. 496 pages. 9.61x6.69x1.26 inches. In Stock.

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Buch. Condition: Neu. Neuware - QUANTILE REGRESSIONA thorough presentation of Quantile Regression designed to help readers obtain richer information from data analysesThe conditional least-square or mean-regression (MR) analysis is the quantitative research method used to model and analyze the relationships between a dependent variable and one or more independent variables, where each equation estimation of a regression can give only a single regression function or fitted values variable. As an advanced mean regression analysis, each estimation equation of the mean-regression can be used directly to estimate the conditional quantile regression (QR), which can quickly present the statistical results of a set nine QR(Ä)s for Ä(tau)s from 0.1 up to 0.9 to predict detail distribution of the response or criterion variable. QR is an important analytical tool in many disciplines such as statistics, econometrics, ecology, healthcare, and engineering.Quantile Regression: Applications on Experimental and Cross Section Data Using EViews provides examples of statistical results of various QR analyses based on experimental and cross section data of a variety of regression models. The author covers the applications of one-way, two-way, and n-way ANOVA quantile regressions, QRs with multi numerical predictors, heterogeneous QRs, and latent variables QRs, amongst others. Throughout the text, readers learn how to develop the best possible quantile regressions and how to conduct more advanced analysis using methods such as the quantile process, the Wald test, the redundant variables test, residual analysis, the stability test, and the omitted variables test. This rigorous volume:\* Describes how QR can provide a more detailed picture of the relationships between independent variables and the quantiles of the criterion variable, by using the least-square regression\* Presents the applications of the test for any quantile of any numerical response or criterion variable\* Explores relationship of QR with heterogeneity: how an independent variable affects a dependent variable\* Offers expert guidance on forecasting and how to draw the best conclusions from the results obtained\* Provides a step-by-step estimation method and guide to enable readers to conduct QR analysis using their own data sets\* Includes a detailed comparison of conditional QR and conditional mean regressionQuantile Regression: Applications on Experimental and Cross Section Data Using EViews is a highly useful resource for students and lecturers in statistics, data analysis, econometrics, engineering, ecology, and healthcare, particularly those specializing in regression and quantitative data analysis.…

Hardcover. Condition: Brand New. 1st edition. 584 pages. 10.00x6.75x1.30 inches. In Stock.

Hardcover. Condition: Brand New. 496 pages. 9.61x6.69x1.26 inches. In Stock. This item is printed on demand.

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Hardcover. Condition: new. Hardcover. A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews. "This book is a reflection of the vast experience and knowledge of the author. It is a useful reference for students and practitioners dealing with cross sectional data analysis . The strength of the book lies in its wealth of material and well structured guidelines ." Prof. Yohanes Eko Riyanto, Nanyang Technological University, Singapore "This is superb and brilliant. Prof. Agung has skilfully transformed his best experiences into new knowledge . creating a new way of understanding data analysis." Dr. I Putu Gede Ary Suta, The Ary Suta Center, Jakarta Basic theoretical concepts of statistics as well as sampling methods are often misinterpreted by students and less experienced researchers. This book addresses this issue by providing a hands-on practical guide to conducting data analysis using EViews combined with a variety of illustrative models (and their extensions). Models having numerically dependent variables based on a cross-section data set (such as univariate, multivariate and nonlinear models as well as non-parametric regressions) are concentrated on. It is shown that a wide variety of hypotheses can easily be tested using EViews. Cross Section and Experimental Data Analysis Using EViews: Provides step-by-step directions on how to apply EViews to cross section data analysis - from multivariate analysis and nonlinear models to non-parametric regressionPresents a method to test for all possible hypotheses based on each modelProposes a new method for data analysis based on a multifactorial design modelDemonstrates that statistical summaries in the form of tabulations are invaluable inputs for strategic decision makingContains 200 examples with special notes and comments based on the authors own empirical findings as well as over 400 illustrative outputs of regressions from EViewsTechniques are illustrated through practical examples from real situationsComes with supplementary material, including work-files containing selected equation and system specifications that have been applied in the book This user-friendly introduction to EViews is ideal for Advanced undergraduate and graduate students taking finance, econometrics, population, or public policy courses, as well as applied policy researchers. A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews. "This book is a reflection of the vast experience and knowledge of the author. It is a useful reference for students and practitioners dealing with cross sectional data analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condition: New. PRINT ON DEMAND pp. xix + 564.