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| What is Statistics? | |
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| Key Statistical Concepts | |
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| Statistical Applications in Business | |
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| Statistics and the Computer | |
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| World Wide Web and Learning Center | |
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| Instructions for the CD-ROM | |
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| Graphical Descriptive Techniques I | |
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| Types of Data and Information | |
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| Describing a Set of Nominal Data | |
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| Describing the Relationship between Two Nominal Variables and Comparing Two or More Nominal Data Sets | |
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| Graphical Descriptive Techniques II | |
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| Graphical Techniques to Describe a Set of Interval Data | |
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| Describing Time-Series Data | |
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| Describing the Relationship between Two Interval Variables | |
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| Art and Science of Graphical Presentations | |
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| Numerical Descriptive Techniques | |
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| Measures of Central Location | |
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| Measures of Variability | |
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| Measures of Relative Standing and Box Plots | |
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| Measures of Linear Relationship | |
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| (Options) Applications In Professional Sports: Baseball | |
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| (Optional) Applications In Finance: Market Model | |
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| Comparing Graphical and Numerical Techniques | |
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| General Guidelines for Exploring Data | |
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| Review Of chapters 2 to 4 | |
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| Data Collection and Sampling | |
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| Methods of Collecting Data | |
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| Sampling | |
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| Sampling Plans | |
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| Sampling and Nonsampling Errors | |
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| Probability | |
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| Assigning Probability to Events | |
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| Joint, Marginal, and Conditional Probability | |
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| Probability Rules and Trees | |
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| Bayes' Law | |
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| Identifying the Correct Method | |
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| Random Variables and Discrete Probability Distributions | |
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| Random Variables and Probability Distributions | |
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| Bivariate Distributions | |
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| (Optional) Applications In Finance: Investment Portfolio Diversification and Asset Allocation | |
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| Binomial Distribution | |
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| Poisson Distribution | |
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| Continuous Probability Distributions | |
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| Probability Density Functions | |
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| Normal Distribution | |
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| (Optional) Exponential Distribution | |
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| Other Continuous Distributions | |
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| Sampling Distributions | |
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| Sampling Distribution of the Mean | |
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| Sampling Distribution of a Proportion | |
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| Sampling Distribution of the Difference between Two Means | |
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| From Here to Inference | |
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| Introduction to Estimation | |
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| Concepts of Estimation | |
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| Estimating the Population Mean when the Population Standard Deviation is Known | |
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| Selecting the Sample Size | |
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| Introduction to Hypothesis Testing | |
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| Concepts of Hypothesis Testing | |
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| Testing the Population Mean when the Population Standard Deviation is Known | |
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| Calculating the Probability of a Type II Error | |
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| The Road Ahead | |
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| Inference about One Population | |
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| Inference about a population Mean when the Standard Deviation is Unknown | |
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| Inference about a Population Variance | |
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| Inference about a Population Proportion | |
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| (Optional) Applications In Marketing: Market Segmentation | |
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| Inference about Two Populations | |
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| Inference about the Difference between Two Means: Independent samples | |
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| Observational and Experimental Data | |
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| Inference about the Difference between Two Means: Matched Pairs Experiment | |
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| Inference about the Ratio of Two Variances | |
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| Inference about the Difference between Two Population Proportions | |
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| Review of Chapters 12 and 13 | |
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| Analysis of Variance | |
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| One Way Analysis of Variance | |
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| Multiple Comparisons | |
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| Analysis of Variance Experimental Designs | |
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| Randomized Blocks (Two Way) Analysis of Variance | |
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| Two-Factor Analysis of Variance | |
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| (Optional) Applications In Operations Management: Finding and Reducing Variation | |
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| Review of chapters 12 to 14 | |
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| Chi-Squared Tests | |
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| Chi-Squared Goodness-of-Fit Test | |
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| Chi-Squared Test of a Contingency Table | |
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| Summary of Tests on Nominal Data | |
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| (Optional) Chi-Squared Test for Normality | |
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| Review of Chapters 12 to 15 | |
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| Simple Linear Regression | |
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| Model | |
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| Estimating the Coefficients | |
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| Error Variable: Required Conditions | |
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| Assessing the Model | |
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| Using the Regression Equation | |
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| Regression Diagnostics - I | |
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| Review of Chapters 12 to 16 | |
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| Multiple Regression | |
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| Model and Required Conditions | |
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| Estimating the Coefficients and Assessing the Model | |
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| Regression Diagnostics - II | |
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| Regression Diagnostics- III (Time Series) | |
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| Review of Chapters 12 to 17 | |
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| Model Building | |
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| Polynomial Models | |
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| Nominal Independent Variables | |
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| (Optional) Applications In Human Resources Management: Pay Equity | |
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| Logistic Regression | |
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| Stepwise Regression | |
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| Model Building | |
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| Nonparametric Statistical Techniques | |
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| Wilcoxon Rank Sum Test | |
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| Sign Test and Wilcoxon Signed Rank Sum Test | |
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| Kruskal-Wallis Test | |
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| Friedman Test | |
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| Spearman Rank Correlation | |
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| Review of Chapters 12 to 19 | |
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| Time-Series Analysis and Forecasting | |
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| Time Series Components | |
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| Smoothing Techniques | |
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| Trend and Seasonal Effects | |
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| Introduction to Forecasting | |
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| Forecasting Models | |
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| Statistical Process Control. 21.1.Process Variation | |
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| Control Charts | |
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| Control Charts for Variables: and S Charts | |
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| Control Charts for Attributes: p Chart. 22:Decision Analysis | |
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| Decision Problem | |
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| Acquiring, Using and Evaluating Additional Information | |
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| Conclusion | |
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| Data File Sample Statistics | |
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| Tables | |
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| Binomial Probabilities | |
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| Poisson Probabilities | |
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| Normal Probabilities | |
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| Critical Values of t | |
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| Critical Values of | |
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| Critical Values of F | |
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| Critical Values of the Studentized Range | |
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| Critical Values for the Durbin-Watson Statistic | |
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| Critical Values for the Wilcoxon Rank Sum Test | |
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| Critical Values for the Wilcoxon Signed Rank Sum Test | |
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| Critical Values for the Spearman Rank Correlation Coefficient | |
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| Control Chart Constants | |
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| Answers to Selected Even-Numbered Exercises | |