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| Introduction and Data Collection | |
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| Overview of Statistics | |
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| Applying Statistics to Business | |
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| How This Text Is Organized | |
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| The Importance of Collecting Data | |
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| Identifying Sources of Data | |
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| Design of Survey Research | |
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| Types of Survey Sampling Methods | |
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| Types of Data | |
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| Evaluating Survey Worthiness | |
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| Presenting Data in Tables and Charts | |
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| Organizing Numerical Data | |
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| Tables and Charts for Numerical Data | |
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| Graphing Bivariate Numerical Data | |
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| Tables and Charts for Categorical Data | |
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| Tabulating and Graphing Bivariate Categorical Data | |
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| Graphical Excellence | |
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| Numerical Descriptive Measures | |
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| Exploring Numerical Data and Their Properties | |
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| Measures of Central Tendency, Variation, and Shape | |
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| Obtaining Descriptive Summary Measures from a Population | |
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| Obtaining Descriptive Summary Measures from a Frequency Distribution | |
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| Exploratory Data Analysis | |
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| The Coefficient of Correlation | |
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| Pitfalls in Numerical Descriptive Measures and Ethical Issues | |
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| Basic Probability | |
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| Basic Probability Concepts | |
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| Conditional Probability | |
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| Bayes' Theorem | |
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| Counting Rules | |
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| Ethical Issues and Probability | |
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| Some Important Discrete Probability Distributions | |
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| The Probability Distribution for a Discrete Random Variable | |
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| Covariance and Its Application in Finance | |
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| Binomial Distribution | |
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| Hypergeometric Distribution | |
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| Poisson Distribution | |
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| CD ROM Topic Using the Poisson Distribution to Approximate the Binomial Distribution | |
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| The Normal Distribution and Other Continuous Distributions | |
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| The Normal Distribution | |
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| Evaluating the Normality Assumption | |
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| The Uniform Distribution | |
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| The Exponential Distribution | |
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| CD ROM Topic The Normal Approximation to the Binomial Distribution | |
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| Sampling Distributions | |
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| Sampling Distribution of the Mean | |
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| Sampling Distribution of the Proportion | |
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| CD ROM Topic Sampling from Finite Populations | |
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| Confidence Interval Estimation | |
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| Confidence Interval Estimation of the Mean (s Known) | |
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| Confidence Interval Estimation of the Mean (s Unknown) | |
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| Confidence Interval Estimation for the Proportion | |
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| Determining Sample Size | |
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| Applications of Confidence Interval Estimation in Auditing | |
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| Confidence Interval Estimation and Ethical Issues | |
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| CD ROM Topic Estimation and Sample Size Determination for Finite | |
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| Fundamentals of Hypothesis Testing: One-Sample Tests | |
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| Hypothesis-Testing Methodology | |
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| Z Test of Hypothesis for the Mean (s Known) | |
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| One-Tailed Tests | |
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| T Test of Hypothesis for the Mean (s Unknown) | |
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| Z Test of Hypothesis for the Proportion | |
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| X2 Test of Hypothesis for the Variance or Standard Deviation | |
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| Potential Hypothesis-Testing Pitfalls and Ethical Issues | |
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| CD ROM Topic The Power of a Test | |
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| Two Sample Tests with Numerical Data | |
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| Comparing Two Independent Samples: Tests for Differences in Two Means | |
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| F Test for Differences in Two Variances | |
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| Comparing Two Related Samples: Tests for the Mean Difference | |
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| Wilcoxon Rank Sum Test: Nonparametric Analysis for Two Independent Populations | |
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| Wilcoxon Signed-Ranks Test: Nonparametric Analysis for Two Related Populations | |
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| Analysis of Variance | |
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| The Completely Randomized Design: One-Way Analysis of Variance | |
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| The Randomized Block Design | |
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| The Factorial Design: Two-Way Analysis of Variance | |
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| Kruskal-Wallis Rank Test: Nonparametric Analysis for the One-Way Design | |
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| Friedman Rank Test: Nonparametric Analysis for the Randomized Block Design | |
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| Tests for Two or More Samples with Categorical Data | |
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| Z Test for the Difference between Two Proportions | |
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| Chi-Square Test for Differences between Two Proportions | |
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| Chi-Square Test for Differences in Among More than Two Proportions | |
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| Chi-Square Test of Independence | |
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| CD ROM Topic Chi-Square Goodness of Fit Tests | |
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| Simple Linear Regression | |
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| Types of Regression Models | |
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| Determining the Simple Linear Regression Equation | |
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| Measures of Variation | |
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| Assumptions | |
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| Residual Analysis | |
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| Measuring Autocorrelation: The Durbin-Watson Statistic | |
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| Inferences about the Slope and Correlation Coefficient | |
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| Estimation of Predicted Values | |
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| Pitfalls in Regression and Ethical Issues | |
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| Computations in Simple Linear Regression | |
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| Introduction to Multiple Regression | |
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| Developing the Multiple Regression Model | |
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| Residual Analysis for the Multiple Regression Model | |
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| Testing for the Significance of the Multiple Regression Model | |
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| Inferences Concerning the Population Regression Coefficients | |
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| Testing Portions of the Multiple Regression Model | |
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| Using Dummy-Variables and Interaction Terms in Regression Models | |
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| Introduction to Logistic Regression | |
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| Multiple Regression Model Building | |
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| The Quadratic Regression Model | |
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| Using Transformations in Regression Models | |
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| Influence Analysis | |
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| Collinearity | |
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| Model Building | |
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| Pitfalls in Multiple Regression and Ethical Issues | |
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| Time-Series Analysis | |
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| The Importance of Business Forecasting | |
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| Component Factors of the Classical Multiplicative Time-Series Model | |
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| Smoothing the Annual Time Series | |
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| Least-Squares Trend Fitting and Forecasting | |
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| The Holt-Winters Method for Trend Fitting and Forecasting | |
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| Autoregressive Modeling for Trend Fitting and Forecasting | |
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| Choosing an Appropriate Forecasting Model | |
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| Time-Series Forecasting of Monthly or Quarterly Data | |
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| Index Numbers | |
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| Pitfalls Concerning Time-Series Analysis | |
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| Decision Making | |
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| Payoff Tables and Decision Trees | |
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| Criteria for Decision Making | |
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| Decision Making with Sample Information | |
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| Utility | |
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| Statistical Applications in Quality and Productivity Management | |
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| Total Quality Management | |
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| Six Sigma�“ Management | |
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| The Theory of Control Charts | |
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| Control Chart for the Proportion of Nonconforming Items The p Chart | |
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| The Red Bead Experiment: Understanding Process Variability | |
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| The c Chart | |
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| Control Charts for the Range and the Mean | |
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| Process Capability | |