Introductory regression analysis : with computer application for business and economics / Allen Webster.

Format:

Book

Author/Creator:

Webster, Allen, author.

Language:

English

Subjects (All):

Commercial statistics.

Economics--Statistical methods.

Economics.

Regression analysis.

Physical Description:

1 online resource (487 p.)

Edition:

1st ed.

Place of Publication:

New York ; London : Routledge, 2013.

Language Note:

English

Summary:

Regression analysis is arguably the single most powerful and widely applicable tool in any effective examination of common business issues. Every day, decision-makers face problems that require constructive actions with significant consequences, and regression procedures can prove a meaningful and valuable asset in the decision-making process. This text is designed to help students achieve a full understanding of regression and the many ways it can be used.Taking into consideration current statistical technology, Introductory Regression Analysis focuses on the use and interpretation

Contents:

Cover; INTRODUCTORY REGRESSION ANALYSIS; Title Page; Copyright Page; Table of Contents; Preface; Chapter 1: A Review of Basic Concepts; Introduction; 1.1 The Importance of Making Systematic Decisions; 1.2 The Process of Statistical Analysis; Data Collection; Organizing the Data; Analyzing the Data; Interpreting the Results; Prediction and Forecasting; 1.3 Our "Arabic" Number System; 1.4 Some Basic Definitions; Populations and Samples; Sampling Error; Sources of Sampling Error: Sampling Bias and Plain Bad Luck; A Sampling Distribution; Types of Variables

1.5 Levels of Data Measurement Nominal Data; Ordinal Data; Interval Data; Ratio Data; 1.6 Properties of Good Estimators; A Good Estimator Is Unbiased; A Good Estimator Is Efficient; A Good Estimator Is Consistent; A Good Estimator Is Sufficient; 1.7 Other Considerations; 1.8 Probability Distributions; 1.9 The Development and Application of Models; 1.10 "In God We Trust-Everybody Else Has to Bring Data"; Chapter Problems; Appendix: Excel Commands and Common Probability Distributions; The Normal Distribution; Student's t-Distribution; The F-Distribution

The Chi-Square DistributionChapter 2: An Introduction to Regression and Correlation Analysis; Introduction; 2.1 The Simple Regression Model; 2.2 Estimating the Model: Ordinary Least Squares; Multiple Regression: A Look Ahead; Calculating the Residuals; 2.3 Why the Process Is Called Ordinary Least Squares; 2.4 Properties and Assumptions of the OLS Model; 2.5 The Gauss-Markov Theorem; 2.6 Measures of Goodness of Fit; The Standard Error of the Estimate; The Coefficient of Determination; How r2 Can Be Used as a Measure of Goodness of Fit; 2.7 Limitations of Regression and Correlation

2.8 Regression Through the Origin2.9 Computer Applications; Using Excel; Using Minitab; Using SPSS; 2.10 Review Problems; Chapter Problems; Conceptual Problems; Computational Problems; Computer Problems; Chapter 3: Statistical Inferences in the Simple Regression Model; Introduction; 3.1 Confidence Interval Estimation; Conditional Mean Interval; The Predictive Interval; Factors that Affect the Width of the Interval; Confidence Interval for the Population Regression Coefficient, β1; Confidence Interval for the Correlation Coefficient, ρ

3.2 Hypothesis Testing: Checking for Statistical Significance Hypothesis Test for the Population Regression Coefficient, β1; The Meaning of the "Level of Significance"; The Hypothesis Test for the Population Correlation Coefficient, ρ; 3.3 Large Samples and the Standard Normal Distribution; 3.4 The p-Value and Its Role in Inferential Analysis; How to Detect and Interpret an Extremely Small p-Value; 3.5 Computer Applications; Using Excel; Using Minitab; Using SPSS; 3.6 Review Problem; Chapter Problems; Conceptual Problems; Computational Problems; Computer Problems

Chapter 4: Multiple Regression: Using Two or More Predictor Variables

Notes:

Description based upon print version of record.

Includes bibliographical references (p. [465]-469) and index.

Description based on metadata supplied by the publisher and other sources.

ISBN:

1-136-59309-8

0-203-18256-1

1-299-27900-7

1-136-59310-1

9780203182567

OCLC:

830161404