Introduction to Business Statistics (with CD-ROM)

by Weiers, Ronald M.

• ISBN13: 9780534385705
• ISBN10: 0534385702
• Format: Hardcover
• Copyright: 2001-12-18
• Publisher: South-Western College Pub

Summary

Highly praised for its clarity and great examples, Weiers's text takes an informal, student-oriented approach to fundamental statistical concepts. Non-technical terminology is used to describe statistical concepts, which are presented in the context of contemporary applications and student experience. Realizing that many business students are intimidated by this course, Weiers provides numerous learning aids and interesting applications drawn from real-world experience common to many students.

Table of Contents

Part 1: BUSINESS STATISTICS: INTRODUCTION AND BACKGROUND

1. A Preview of Business Statistics

Introduction

Statistics: Yesterday and Today

Descriptive Versus Inferential Statistics

Types of Variables and Scales of Measurement

Statistics in Business Decisions

Business Statistics: Tools Versus Tricks

Summary

2. Visual Description of Data

Introduction

The Data Array and the Frequency Distribution

The Stem and Leaf Display and the Dotplot

Visual Representation of the Data

The Scatter Diagram

Tabulation, Contingency Tables, and the Excel PivotTable Wizard

Summary

3. Statistical Description of Data

Introduction

Statistical Description: Measures of Central Tendency

Statistical Description: Measures of Dispersion

Additional Dispersion Topics

Descriptive Statistics from Grouped Data

Statistical Measures of Association

Summary

4. Data Collection and Sampling Methods

Introduction

Research Basics

Survey Research

Experimentation and Observational Research

Secondary Data

The Basics of Sampling

Sampling Methods

Summary

Part 2: PROBABILITY

5. Probability: Review of Basic Concepts

Introduction

Probability: Terms and Approaches

Unions and Intersections of Events

Addition Rules for Probability

Multiplication Rules for Probability

Bayes' Theorem and the Revision of Probabilities

Counting: Permutations and Combinations

Summary

6. Discrete Probability Distributions

Introduction

The Binomial Distribution

The Poisson Distribution

Simulating Observations from a Discrete Probability Distribution

Summary

7. Continuous Probability Distributions

Introduction

The Normal Distribution

The Standard Normal Distribution

The Normal Approximation to the Binomial Distribution

The Exponential Distribution

Simulating Observations from a Continuous Probability Distribution

Summary

Part 3: SAMPLING DISTRIBUTION AND ESTIMATION

8. Sampling Distributions

Introduction

A Review of Sampling Distributions

The Sampling Distribution of the Mean

The Sampling Distribution of the Proportion

Sampling Distributions When the Population is Finite

Computer Simulation of Sampling Distributions

Summary

9. Estimation from Simple Data

Introduction

Point Estimates

A Preview of Interval Estimates

Confidence Interval Estimates for the Mean: s Known

Confidence Interval Estimates for the Mean: s Unknown

Confidence Interval Estimates for the Population Proportion

Sample Size Determination

When the Population is Finite

Summary

Part 4: HYPOTHESIS TESTING

10. Hypothesis Tests Involving a Simple Mean or Proportion

Introduction

Hypothesis Testing: Basic Procedures

Testing a Mean, Population Standard Deviation Known

Confidence Intervals and Hypothesis Testing

Testing a Mean, Population Standard Deviation Unknown

Testing a Proportion

The Power of a Hypothesis Test

Summary

11. Hypothesis Tests Involving Two Simple Means or Proportions

Introduction

The Pooled-Variances t-Test for Comparing the Means of Two Independent Samples

The Unequal-Variances t-Test for Comparing the Means of Two Independent Samples

The z-Test for Comparing the Means of Two Independent Samples

Comparing Two Means When the Samples are Dependent

Comparing Two Sample Proportions

Comparing the Variances of Two Independent Samples

Summary

12. Analysis of Variance Tests

Introduction

Analysis of Variance: Basic Concepts

One-Way Analysis of Variance

The Randomized Block Design

Two-Way Analysis of Variance

Summary

13. Chi-Square Applications

Introduction

Basic Concepts in Chi-Square Testing

Tests for Goodness-of-Fit and Normality

Testing the Independence of Two Variables

Comparing Proportions from k Independent Samples

Estimation and Tests Regarding the Population Variance

Summary

14. Nonparametric Methods

Introduction

Wilcoxon Signed Rank Test for One Sample

Wilcoxon Signed Rank Test for Comparing Paired Samples

Wilcoxon Rank Sum Test for Comparing Two Independent Samples

Kruskal-Wallis Test for Comparing More Than Two Independent Samples

Friedman Test for the Randomized Block Design

Other Nonparametric Methods

Summary

Part 5: REGRESSION, MODEL BUILDING, AND TIME SERIES

15. Simple Linear Regression and Correlation

Introduction

The Simple Linear Regression Model

Interval Estimation Using the Sample Regression Line

Correlation Analysis

Estimation and Tests Regarding the Sample Regression Line

Additional Topics in Regression and Correlation Analysis

Summary

16. Multiple Regression and Correlation

Introduction

The Multiple Regression Model

Interval Estimation in Multiple Regression

Multiple Correlation Analysis

Significance Tests in Multiple Regression and Correlation

Overview of the Computer Analysis and Interpretation

Additional Topics in Multiple Regression and Correlation

Summary

17. Model Building

Introduction

Polynomial Models with One Quantitative Predictor Variable

Polynomial Models with Two Quantitative Predictor Variables

Qualitative Variables

Data Transformations

Multicollinearity

Stepwise Regression

Selecting a Model

Summary

18. Time Series, Forecasting and Index Numbers

Introduction

Time Series

Smoothing Techniques

Seasonal Indexes

Forecasting

Evaluating Alternative Models: MAD and MSE

Autocorrelation, the Durbin-Watson Test, and Autoregressive Forecasting

Index Numbers

Summary

Part 6: SPECIAL TOPICS

19. Decision Theory

Introduction

Structuring the Decision Situation

Non-Bayesian Decision Making

Bayesian Decision Making

The Opportunity Loss Approach

Incremental Analysis and Inventory Decisions

Summary

Appendix: The Expected Value of Imperfect Information

20. Total Quality Mangement

Introduction

A Historical Perspective and Defect Detection

The Emergence of Total Quality Management

Practicing Total Quality Management

Some Statistical Tools for Total Quality Management

Statistical Process Control: The Concepts

Control Charts for Variables

Control Charts for Attributes

More on Computer-Assisted Statistical Process Control

Summary