Introduction to Business Statistics (with CD-ROM)
, by Weiers, Ronald M.Note: Supplemental materials are not guaranteed with Rental or Used book purchases.
- ISBN: 9780534385705 | 0534385702
- Cover: Hardcover
- Copyright: 12/18/2001
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.
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 |
What is included with this book?
The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.