Cross Section and Experimental Data Analysis Using EViews

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 regression

• Presents a method to test for all possible hypotheses based on
  each model

• Proposes a new method for data analysis based on a
  multifactorial design model

• Demonstrates that statistical summaries in the form of
  tabulations are invaluable inputs for strategic decision
  making

• Contains 200 examples with special notes and comments based on
  the author's own empirical findings as well as over 400
  illustrative outputs of regressions from EViews

• Techniques are illustrated through practical examples from real
  situations

• Comes 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.

Autorentext

I Gusti Ngurah Agung is a Lecturer and Academic Advisor at the Graduate School of Management, Faculty of Economics at the University of Indonesia. He has been teaching mathematical statistics and applied statistics since 1960 at the Makassar Public University as well as Hassanudin University, Makassar, since 1987 at the Faculty of Economics, University of Indonesia, and since 2006 at the Graduate School of Planning, Strategy and Public Policy, University of Indonesia. Areas of interest include population studies, education, public health, economics, management and finance. Agung has authored one applied statistics textbook in English and more than 10 pocket books in Indonesian. He holds a BSc in Mathematical Education from Hassanudin University, a Masters in Mathematics from the New Mexico State University and a second Masters in mathematical statistics as well as a PhD in biostatistics from the University of North Carolina at Chapel Hill.

Zusammenfassung
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 regression
• Presents a method to test for all possible hypotheses based on each model
• Proposes a new method for data analysis based on a multifactorial design model
• Demonstrates that statistical summaries in the form of tabulations are invaluable inputs for strategic decision making
• Contains 200 examples with special notes and comments based on the author's own empirical findings as well as over 400 illustrative outputs of regressions from EViews
• Techniques are illustrated through practical examples from real situations
• Comes 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.

Inhalt
Preface. 1 Misinterpretation of Selected Theoretical Concepts of Statistics.

1.1 Introduction.

1.2 What is a Population?

1.3 A Sample and Sample Space.

1.4 Distribution of a Random Sample Space.

1.5 What is a Random Variable?

1.6 Theoretical Concept of a Random Sample.

1.7 Does a Representative Sample Really Exist?

1.8 Remarks on Statistical Powers and Sample Sizes.

1.9 Hypothesis and Hypothesis Testing.

1.10 Groups of Research Variables.

1.11 Causal Relationship between Variables.

1.12 Misinterpretation of Selected Statistics.

2 Simple Statistical Analysis but Good for Strategic Decision Making.

2.1 Introduction.

2.2 A Single Input for Decision Making.

2.3 Data Transformation.

2.4 Biserial Correlation Analysis.

2.5 One-Way Tabulation of a Variable.

2.6 Two-Way Tabulations.

2.7 Three-Way Tabulation.

2.8 Special Notes and Comments.

2.9 Special Cases of the N-Way Incomplete Tables.

2.10 Partial Associations.

2.11 Multiple Causal Associations Based on Categorical Variables.

2.12 Seemingly Causal Model Based on Categorical Variables.

2.13 Alternative Descriptive Statistical Summaries.

2.14 How to Present Descriptive Statistical Summary?

2.15 General Seemingly Causal Model.

2.16 Empirical Studies Presenting Descriptive Statistical Summaries.

3 One-Way Proportion Models.

3.1 Introduction.

3.2 One-Way Proportion Models Based on a 2 2 Table.

3.3 Binary Choice Models Based on a K 2 Table.

3.4 Binary Logit Models Based on N-Way Tabulation.

3.5 General Binary Choice Models.

3.6 Special Notes and Comments.

3.7 Association between Categorical Variables.

3.8 One-Way Binary Choice Models Based on N-Way Tabulation.

3.9 Special Notes and Comments on Binary Choice Models.

4 N-Way Cell-Proportion Models.

4.1 Introduction.

4.2 The N-Way Tabulation of Proportions.

4.3 The 2 2 Factorial Model of Proportion…