What is Statistics? | |

Key Statistical Concepts | |

Statistical Applications in Business | |

Statistics and the Computer | |

World Wide Web and Learning Center | |

Instructions for the CD-ROM | |

Graphical Descriptive Techniques I | |

Types of Data and Information | |

Describing a Set of Nominal Data | |

Describing the Relationship between Two Nominal Variables and Comparing Two or More Nominal Data Sets | |

Graphical Descriptive Techniques II | |

Graphical Techniques to Describe a Set of Interval Data | |

Describing Time-Series Data | |

Describing the Relationship between Two Interval Variables | |

Art and Science of Graphical Presentations | |

Numerical Descriptive Techniques | |

Measures of Central Location | |

Measures of Variability | |

Measures of Relative Standing and Box Plots | |

Measures of Linear Relationship | |

(Options) Applications In Professional Sports: Baseball | |

(Optional) Applications In Finance: Market Model | |

Comparing Graphical and Numerical Techniques | |

General Guidelines for Exploring Data | |

Review Of chapters 2 to 4 | |

Data Collection and Sampling | |

Methods of Collecting Data | |

Sampling | |

Sampling Plans | |

Sampling and Nonsampling Errors | |

Probability | |

Assigning Probability to Events | |

Joint, Marginal, and Conditional Probability | |

Probability Rules and Trees | |

Bayes' Law | |

Identifying the Correct Method | |

Random Variables and Discrete Probability Distributions | |

Random Variables and Probability Distributions | |

Bivariate Distributions | |

(Optional) Applications In Finance: Investment Portfolio Diversification and Asset Allocation | |

Binomial Distribution | |

Poisson Distribution | |

Continuous Probability Distributions | |

Probability Density Functions | |

Normal Distribution | |

(Optional) Exponential Distribution | |

Other Continuous Distributions | |

Sampling Distributions | |

Sampling Distribution of the Mean | |

Sampling Distribution of a Proportion | |

Sampling Distribution of the Difference between Two Means | |

From Here to Inference | |

Introduction to Estimation | |

Concepts of Estimation | |

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

Selecting the Sample Size | |

Introduction to Hypothesis Testing | |

Concepts of Hypothesis Testing | |

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

Calculating the Probability of a Type II Error | |

The Road Ahead | |

Inference about One Population | |

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

Inference about a Population Variance | |

Inference about a Population Proportion | |

(Optional) Applications In Marketing: Market Segmentation | |

Inference about Two Populations | |

Inference about the Difference between Two Means: Independent samples | |

Observational and Experimental Data | |

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

Inference about the Ratio of Two Variances | |

Inference about the Difference between Two Population Proportions | |

Review of Chapters 12 and 13 | |

Analysis of Variance | |

One Way Analysis of Variance | |

Multiple Comparisons | |

Analysis of Variance Experimental Designs | |

Randomized Blocks (Two Way) Analysis of Variance | |

Two-Factor Analysis of Variance | |

(Optional) Applications In Operations Management: Finding and Reducing Variation | |

Review of chapters 12 to 14 | |

Chi-Squared Tests | |

Chi-Squared Goodness-of-Fit Test | |

Chi-Squared Test of a Contingency Table | |

Summary of Tests on Nominal Data | |

(Optional) Chi-Squared Test for Normality | |

Review of Chapters 12 to 15 | |

Simple Linear Regression | |

Model | |

Estimating the Coefficients | |

Error Variable: Required Conditions | |

Assessing the Model | |

Using the Regression Equation | |

Regression Diagnostics - I | |

Review of Chapters 12 to 16 | |

Multiple Regression | |

Model and Required Conditions | |

Estimating the Coefficients and Assessing the Model | |

Regression Diagnostics - II | |

Regression Diagnostics- III (Time Series) | |

Review of Chapters 12 to 17 | |

Model Building | |

Polynomial Models | |

Nominal Independent Variables | |

(Optional) Applications In Human Resources Management: Pay Equity | |

Logistic Regression | |

Stepwise Regression | |

Model Building | |

Nonparametric Statistical Techniques | |

Wilcoxon Rank Sum Test | |

Sign Test and Wilcoxon Signed Rank Sum Test | |

Kruskal-Wallis Test | |

Friedman Test | |

Spearman Rank Correlation | |

Review of Chapters 12 to 19 | |

Time-Series Analysis and Forecasting | |

Time Series Components | |

Smoothing Techniques | |

Trend and Seasonal Effects | |

Introduction to Forecasting | |

Forecasting Models | |

Statistical Process Control. 21.1.Process Variation | |

Control Charts | |

Control Charts for Variables: and S Charts | |

Control Charts for Attributes: p Chart. 22:Decision Analysis | |

Decision Problem | |

Acquiring, Using and Evaluating Additional Information | |

Conclusion | |

Data File Sample Statistics | |

Tables | |

Binomial Probabilities | |

Poisson Probabilities | |

Normal Probabilities | |

Critical Values of t | |

Critical Values of | |

Critical Values of F | |

Critical Values of the Studentized Range | |

Critical Values for the Durbin-Watson Statistic | |

Critical Values for the Wilcoxon Rank Sum Test | |

Critical Values for the Wilcoxon Signed Rank Sum Test | |

Critical Values for the Spearman Rank Correlation Coefficient | |

Control Chart Constants | |

Answers to Selected Even-Numbered Exercises | |

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