Managerial statistics

This worldwide best-selling business statistics book teaches readers how to apply statistics to real business problems through the author's unique three-step approach to problem solving. Readers learn to IDENTIFY the right technique by focusing on the problem objective and data type. They then learn to COMPUTE the statistics either by hand, using Excel, or using MINITAB. Finally, they INTERPRET the results in the context of the problem. Keller's approach enhances user comprehension as well as practical skills.

1 What is Statistics?

1.1 Key Statistical Concepts

1.2 Statistical Applications in Business

1.3 Statistics and the Computer

1.4 World Wide Web and Learning Center

Appendix 1 Instructions for the CD-ROM

2 Graphical Descriptive Techniques I

2.1 Types of Data and Information

2.2 Describing a Set of Nominal Data

2.3 Describing the Relationship between Two Nominal Variables and Comparing Two or More

Nominal Data Sets

3 Graphical Descriptive Techniques II

3.1 Graphical Techniques to Describe a Set of Interval Data

3.2 Describing Time-Series Data

3.3 Describing the Relationship between Two Interval Variables

3.4 Art and Science of Graphical Presentations

4 Numerical Descriptive Techniques

4.1 Measures of Central Location

4.2 Measures of Variability

4.3 Measures of Relative Standing and Box Plots

4.4 Measures of Linear Relationship

4.5 (Options) Applications in Professional Sports: Baseball

4.6 (Optional) Applications in Finance: Market Model

4.7 Comparing Graphical and Numerical Techniques

4.8 General Guidelines for Exploring Data

Appendix 4 Review Of chapters 2 to 4

5 Data Collection and Sampling

5.1 Methods of Collecting Data

5.2 Sampling

5.3 Sampling Plans

5.4 Sampling and Nonsampling Errors

6 Probability

6.1 Assigning Probability to Events

6.2 Joint, Marginal, and Conditional Probability

6.3 Probability Rules and Trees

6.4 BayesÆ Law

6.5 Identifying the Correct Method

7 Random Variables and Discrete Probability Distributions

7.1 Random Variables and Probability Distributions

7.2 Bivariate Distributions

7.3 (Optional) Applications in Finance: Investment Portfolio Diversification and Asset Allocation

7.4 Binomial Distribution

7.5 Poisson Distribution

8 Continuous Probability Distributions

8.1 Probability Density Functions

8.2 Normal Distribution

8.3 (Optional) Exponential Distribution

8.4 Other Continuous Distributions

9 Sampling Distributions

9.1 Sampling Distribution of the Mean

9.2 Sampling Distribution of a Proportion

9.3 Sampling Distribution of the Difference between Two Means

9.4 From Here to Inference

10 Introduction to Estimation

10.1 Concepts of Estimation

10.2 Estimating the Population Mean when the Population Standard Deviation is Known

10.3 Selecting the Sample Size

11 Introduction to Hypothesis Testing

11.1 Concepts of Hypothesis Testing

11.2 Testing the Population Mean when the Population Standard Deviation is Known

11.3 Calculating the Probability of a Type II Error

11.4 The Road Ahead

12 Inference about One Population

12.1 Inference about a population Mean when the Standard Deviation is Unknown

12.2 Inference about a Population Variance

12.3 Inference about a Population Proportion

12.4 (Optional) APplications in Marketing: Market Segmentation

13 Inference about Two Populations

13.1 Inference about the Difference between Two Means: Independent samples

13.2 Observational and Experimental Data

13.3 Inference about the Difference between Two Means: Matched Pairs Experiment

13.4 Inference about the Ratio of Two Variances

13.5 Inference about the Difference between Two Population Proportions

Appendix 13 Review of Chapters 12 and 13

14 Analysis of Variance

14.1 One Way Analysis of Variance

14.2 Multiple Comparisons

14.3 Analysis of Variance Experimental Designs

14.4 Randomized Blocks (Two Way) Analysis of Variance

14.5 Two-Factor Analysis of Variance

14.6 (Optional) Applications in Operations Management: Finding and Reducing Variation

Appendix 14 Review of chapters 12 to 14

15 Chi-Squared Tests

15.1 Chi-Squared Goodness-of-Fit Test

15.2 Chi-Squared Test of a Contingency Table

15.3 Summary of Tests on Nominal Data

15.4 (Optional) Chi-Squared Test for Normality

Appendix 15 Review of Chapters 12 to 15

16 Simple Linear Regression

16.1 Model

16.2 Estimating the Coefficients

16.3 Error Variable: Required Conditions

16.4 Assessing the Model

16.5 Using the Regression Equation

16.6 Regression Diagnostics ? I

Appendix 16 Review of Chapters 12 to 16

17 Multiple Regression

17.1 Model and Required Conditions

17.2 Estimating the Coefficients and Assessing the Model

17.3 Regression Diagnostics ? II

17.4 Regression Diagnostics- III (Time Series)

Appendix 17 Review of Chapters 12 to 17

18 Model Building

18.1 Polynomial Models

18.2 Nominal Independent Variables

18.3 (Optional) Applications in Human Resources Management: Pay Equity

18.4 Logistic Regression

18.5 Stepwise Regression

18.6 Model Building

19 Nonparametric Statistical Techniques

19.1 Wilcoxon Rank Sum Test

19.2 Sign Test and Wilcoxon Signed Rank Sum Test

19.3 Kruskal-Wallis Test

19.4 Friedman Test

19.5 Spearman Rank Correlation

Appendix 19 Review of Chapters 12 to 19

20 Time-Series Analysis and Forecasting

20.1 Time Series Components

20.2 Smoothing Techniques

20.3 Trend and Seasonal Effects

20.4 Introduction to Forecasting

20.5 Forecasting Models

21 Statistical Process Control

21.1 rocess Variation

21.2 Control Charts

21.3 Control Charts for Variables: and S Charts

21.4 Control Charts for Attributes: p Chart

22 Decision Analysis

22.1 Decision Problem

21.2 Acquiring, Using and Evaluating Additional Information

23 Conclusion

Appendix A Data File Sample Statistics

Appendix B Tables

1 Binomial Probabilities

2 Poisson Probabilities

3 Normal Probabilities

4 Critical Values of t

5 Critical Values of

6 Critical Values of F

7 Critical Values of the Studentized Range

8 Critical Values for the Durbin-Watson Statistic

9 Critical Values for the Wilcoxon Rank Sum Test

10 Critical Values for the Wilcoxon Signed Rank Sum Test

11 Critical Values for the Spearman Rank Correlation Coefficient

12 Control Chart Constants

Appendix C Answers to Selected Even-Numbered Exercises

Mevcut:*

Bound With These Titles

On Order

Özet

Özet

Table of Contents