Otto von Bis

CONTENT DESCRIPTION

Applied Statistical Modeling
Prerequisite: College level introductory statistics course or equivalent.

This electronic textbook explores introductory statistical modeling and analysis techniques for aiding managerial decision making. Topics include: univariate- and multivariate linear and polynomial regression, analysis of variance, correlation and non-parametric techniques. Selected software packages are used in exercises and in a statistical modeling project.

Copyright StatSoft, Inc.

RECOMMENDED TEXTBOOKS AND SOURCES (no printed textbook required)

• Electronic Statistics Textbook, StatSoft Inc., Tulsa, OK, (2006). WEB: http://www.statsoft.com/textbook/stathome.html
• Microsoft Office 2003, or later, copyright Microsoft Corporation (c 1985-2003). Please make sure that Microsoft Excel is installed with Data Analysis tools and Function add-ins.
• STATISTICA for Windows, Student Edition, StatSoft Inc., Tulsa, OK, (2006). WEB: http://www.statsoft.com/
• Statistics for Managers using Microsoft Excel, by Levine, Berenson and Stephan, 2nd Edition, Prentice Hall (1999), Chapters 7-15.

CONTENT DESIGN

The emphasis is placed on understanding the basics of statistical analysis and modeling, use of statistical modeling and statistical techniques in practical problems, utilization of software, as well as interpretation of software output and results.

The electronic book is organized into six learning Modules. Each learning Module in turn is divided into sections as follows:

• Learning objectives
• Overview of the Learning Module Content
• Discussion
• Exercises or Short Problems
• Quiz

Note: This Electronic Textbook is based on class room materials from 20 years of graduate level teaching of statistical-, regression and quantitave modeling at the University of Michigan-Dearborn and the University of Michigan. The 1st Edition of the textbook has been used by students, faculty, and practitioners around the world. The book should be considered an introductory regression modeling book. The book is simple, intuitive, and all results of examples, cases and animations can be replicated by the user. Quizzes are not available with this Electonic Textbook version. I have left all references to quizzes in the text, so that you plan to add your own quizzes, if you are an instructor, or use those statements as 'check points' when moving forward. If you find the book fun and useful, find errors or have comments for improvement, please email me at gary.waissi@asu.edu

TOPICS

Module 1 - Review of Hypothesis Testing and Confidence Intervals
• Learning objectives
• Overview of hypothesis testing, confidence intervals and correlation
• Review of hypothesis testing, confidence intervals and correlation Particular attention is given to the one- and two sample z- and t-tests and confidence intervals for dependent and independent populations, as well as to the F-test. In addition, the concept of correlation and Pearson correlation are reviewed.
• Examples
• Quiz 1 (10 points)

Module 2 - Simple Linear Regression
• Learning objectives
• Overview of the concept of regression
• Simple (univariate) linear regression Model assumptions, model development, parameter estimation, parameter- and model testing, OLS, residual analysis, interpretation of results and model improvement.
• Examples
• Case
• Quiz 2 (10 points)

Module 3 - Multiple Linear Regression
• Learning objectives
• Overview of the concept of multivariate regression
• Multivariate linear regression Model assumptions, model development, parameter estimation, parameter- and model testing, OLS, residual analysis, interpretation of results and model improvement.
• Examples
• Case
• Quiz 3 (10 points)

Module 4 - Polynomial Regression
• Learning objectives
• Overview of the concept of polynomial- and non-linear univariate- and multivariate regression
• Polynomial- and non-linear regression Model assumptions, model development, parameter estimation, parameter- and model testing, OLS, residual analysis, interpretation of results and model improvement.
• Examples
• Case
• Quiz 4 (10 points)

Module 5 - Project (data file available upon request)
• Learning objectives
• Overview of the Statistical Modeling Project
• Discussion of project goals, requirements and limitations.
• Project Report (25 points)

Module 6 - Analysis of Variance (ANOVA)
• Learning objectives
• Overview of the concept of Analysis of Variance
• One-way and two-way ANOVA Model assumptions, model development, interpretation of results.
• Examples
• Case
• Quiz 5 (10 points)

Final Examination (25 points)
Have fun in learning statistical modeling!!!.