Introduction and Data Collection | |
Using Statistics: Good Tunes | |
Basic Concepts of Statistics | |
The Growth of Statistics and Information Technology | |
How This Text Is Organized | |
The Importance of Collecting Data | |
Identifying Sources of Data | |
Types of Data | |
Levels of Measurement and Types of Measurement Scales | |
Summary | |
Introduction to Using Software | |
Presenting Data in Tables and Charts | |
Using Statistics: Comparing the Performance of Mutual Funds | |
Tables and Charts for Categorical Data | |
The Summary Table | |
The Bar Chart | |
The Pie Chart | |
The Pareto Diagram | |
Organizing Numerical Data | |
The Ordered Array | |
The Stem-and-Leaf Display | |
Tables and Charts for Numerical Data | |
The Frequency Distribution | |
The Relative Frequency Distribution and the Percentage Distribution | |
The Cumulative Distribution | |
The Histogram | |
The Polygon | |
The Cumulative Percentage Polygon (Ogive) | |
Cross Tabulations | |
The Contingency Table | |
The Side-by-Side Bar Chart | |
Scatter Diagrams and Time Series Plots | |
The Scatter diagram | |
The Time series plot | |
Misusing Graphs and Ethical Issues | |
Summary | |
Using Software for Tables and Charts | |
Numerical Descriptive Measures | |
Using Statistics: Comparing the Performance of Mutual Funds | |
Measures of Central Tendency, Variation, and Shape | |
The Mean | |
The Median | |
The Mode | |
Quartiles | |
The Geometric Mean | |
The Range | |
The Interquartile Range | |
The Variance and Standard Deviation | |
The Coefficient of Variation | |
Shape | |
Visual Explorations: Exploring Descriptive Statistics | |
Microsoft Excel Descriptive Statistics Output | |
Minitab Descriptive Statistics Output | |
Descriptive Numerical Measures for a Population | |
The Population Mean | |
The Population Variance and Standard Deviation | |
The Empirical Rule | |
The Chebychev Rule | |
Computing Descriptive Numerical Measures from a Frequency Distribution | |
Exploratory Data Analysis | |
The Five-Number Summary | |
The Box-and-Whisker Plot | |
The Covariance and the Coefficient of Correlation | |
The Covariance | |
The Coefficient of Correlation | |
Pitfalls in Numerical Descriptive Measures and Ethical Issues | |
Summary | |
Using Software for Descriptive Statistics | |
Basic Probability | |
Using Statistics: The Consumer Electronics Company | |
Basic Probability Concepts | |
Sample Spaces and Events | |
Contingincy Tables and Venn Diagrams | |
Simple (Marginal) Probability | |
Joint Probability | |
General Addition Rule | |
Conditional Probability | |
Computing Conditional Probabilities | |
Decision Trees | |
Statistical Independence | |
Multiplication Rule | |
Bayes' Theorem | |
Counting Rules | |
Ethical Issues and Probability | |
Summary | |
Using Software for Basic Probability | |
Some Important Discrete Probability Distributions | |
Using Statistics: The Accounting Information System of the Saxon Plumbing Company | |
The Probability Distribution for a Discrete Random Variable | |
Expected Value of a Discrete Random Variable | |
Variance and Standard Deviation of a Discrete Random Variable | |
Covariance and Its Application in Finance | |
The Covariance | |
The Expected Value, Variance, and Standard Deviation of the Sum of Two Random Variables | |
Portfolio Expected Return and Portfolio Risk | |
Binomial Distribution | |
Poisson Distribution | |
Hypergeometric Distribution | |
CD ROM Topic : Using the Poisson Distribution to Approximate the Binomial Distribution | |
Summary | |
Using Software for the Covariance and for Discrete Probability Distributions | |
The Normal Distribution and Other Continuous Distributions | |
Using Statistics: Download Time for a Web Site Home Page | |
Continuous Probability Distributions | |
The Normal Distribution | |
Evaluating Normality | |
Evaluating the Properties | |
Constructing the Normal Probability Plot | |
The Uniform Distribution | |
The Exponential Distribution | |
The Normal Approximation to the Binomial Distribution | |
Need for a Correction for Continuity Adjustment | |
Approximating the Binomial Distribution | |
Computing a Probability Approximation for an Individual Value | |
Summary | |
Using Software with Continuous Probability Distributions | |
Sampling Distributions | |
Using Statistics: The Oxford Cereal Company Packaging Process | |
Sampling Distributions | |
Sampling Distribution of the Mean | |
The Unbiased Property of the Sample Mean | |
Standard Error of the Mean | |
Sampling from Normally Distributed Populations | |
Sampling from Nonnormally Distributed Populations The Central Limit Theorem | |
Sampling Distribution of the Proportion | |
Types of Survey Sampling Methods | |
Simple Random Sample | |
Systematic Sample | |
Stratified Sample | |
The Cluster Sample | |
Evaluating Survey Worthiness | |
Survey Errors | |
Ethical Issues | |
CD ROM Topic Sampling from Finite Populations | |
Summary | |
Using Software for Sampling Distributions | |
Confidence Interval Estimation | |
Using Statistics: Auditing Invoices at the Saxon Home Improvement Company | |
Confidence Interval Estimation of the Mean (Ãâ Known) | |
Confidence Interval Estimation of the Mean (Ãâ Unknown) | |
Student's t Distribution | |
The Concept of Degrees of Freedom | |
The Confidence Interval Statement | |
Confidence Interval Estimation for the Proportion | |
Determining Sample Size | |
Sample Size Determination for the Mean | |
Sample Size Determination for the Proportion | |
Applications of Confidence Interval Estimation in Auditing | |
Estimating the Population Total Amount | |
Difference Estimation | |
Confidence Interval Estimation and Ethical Issues | |
CD ROM Topic: Estimation and Sample Size Determination for Finite Populations | |
Summary | |
Using Software for Confidence Interval Estimation | |
Fundamentals of Hypothesis Testing | |
Using Statistics: The Oxford Cereal Company Packaging Process | |
Hypothesis-Testing Methodology | |
The Null and Alternative Hypotheses | |
The Critical Value of the Test Statistic | |
Regions of Rejection and Nonrejection | |
Risks in Decision Making using Hypothesis Testing Methodology | |
Z Test of Hypothesis for the Mean (Ãâ Known) | |
The Critical Value Approach to Hypothesis Testing | |
The p-Value Approach to Hypothesis Testing | |
A Connection between Confidence Interval Estimation and Hypothesis Testing One-Tailed Tests | |
One-Tail Tests | |
The Critical Value Approach | |
The p-Value Approach | |
t Test of Hypothesis for the Mean (Ãâ Unknown) | |
Z Test of Hypothesis for the Proportion | |
The Power of a Test | |
Potential Hypothesis-Testing Pitfalls and Ethical Issues | |
Summary | |
Using Software for One-Sample Tests of Hypothesis | |
Two-Sample Tests | |
Comparing The Means of Two Independent Samples | |
Z test for the Difference between Two Means | |
Pooled - Variance test for the Difference between Two Means | |
Confidence Interval Estimate for the Difference between the Means of two Independent Groups | |
Separate - Variance test for the Difference between Two Means | |
Comparing the Means of Two Related Populations | |
The Paired Test | |
Confidence Interval Estimate for the Mean Difference | |
Comparing Two Population Proportions | |
Z Test for the Difference between Two Proportions | |
Confidence Interval Estimate for the Difference between Two Proportions | |
F Test for the Difference between Two Variances | |
Finding Lower-Tail Critical Values | |
Summary | |
Using Software for Two-Sample Tests of Hypothesis for Numerical Data | |
Analysis of Variance | |
Using Statistics: The Perfect Parachute Company | |
The Completely Randomized Design: One-Way Analysis of Variance | |
F Test for Differences in More than Two Means | |
Multiple Comparisons: The Tukey-Kramer Procedure | |
ANOVA Assumptions | |
Levene's Test for Homogeneity of Variance | |
The Randomized Block Design | |
Tests for the Treatment and Block Effects | |
Multiple Comparisons: The Tukey Procedure | |
The Factorial Design: Two-Way Analysis of Variance | |
Testing for Factor and Interaction Effects | |
Interpreting Interaction Effects | |
Multiple Comparisons: The Tukey Procedure | |
Summary | |
Using Software for ANOVA | |
Chi-Square Tests and Nonparametric Tests | |
Using Statistics: Guest Satisfaction at T. C. Resort Properties | |
Chi-Square Test for Differences between Two Proportions (Independent Samples) | |
Chi-Square Test for Differences among More than Two Proportions | |
Chi-Square Test of Independence | |
McNemar Test for the Difference between Two Proportions (Related Samples) | |
Chi-Square Test for a Variance or Standard Deviation | |
Chi-Square Goodness of Fit Tests | |
Chi-Square Goodness of Fit Test for the Poisson Distribution | |
Chi-Square Goodness of Fit Test for the Normal Distribution | |
Wilcoxon Rank Sum Test: Nonparametric Analysis for Two Independent Populations | |
Wilcoxon Signed Ranks Test: Nonparametric Analysis for Two Related Populations | |
Kruskal-Wallis Rank Test: Nonparametric Analysis for the One-Way Design | |
Friedman Rank Test: Nonparametric Analysis for the Randomized Block Design | |
Summary | |
Using Software for Chi-Square Tests and Nonparametric Tests | |
Simple Linear Regression | |
Using Statistics: Forecasting Sales at the Sunflowers Clothing Stores | |
Types of Regression Models | |
The Least-Squares Method | |
Visual Explorations: Exploring Simple Linear Regression Coefficients | |
Predictions in Regression Analysis: Interpolation versus Extrapolation | |
Measures of Variation | |
Computing the Sum of Squares | |
The Coefficient of Determination | |
Standard Error of the Estimate | |
Assumptions | |
Residual Analysis | |
Evaluating the Assumptions | |
Measuring Autocorrelation: The Durbin-Watson Statistic | |
Residual Plots to Detect Autocorrelation | |
The Durbin-Watson Statistic | |
Inferences about the Slope and Correlation Coefficient Test for the Slope | |
F Test for the Slope | |
Confidence Interval Estimate for the Slope | |
t Test for the Correlation Coefficient | |
Estimation of Predicted Values | |
The Confidence Interval Estimate | |
The Prediction Interval | |
Pitfalls in Regression and Ethical Issues | |
Summary | |
Using Software for Simple Linear Regression | |
Introduction to Multiple Regression | |
Using Statistics: Predicting OmniPower Sales | |
Developing the Multiple Regression Model | |
Interpreting the Regression Coefficients | |
Predicting the Dependent Variable Y | |
R2, Adjusted R2, and the Overall F test 000 | |
Coefficients of Multiple Determination | |
Test for the Significance of the overall Multiple Regression Model | |
Residual Analysis for the Multiple Regression Model | |
Inferences Concerning the Population Regression Coefficients | |
Test of Hypothesis | |
Confidence Interval Estimation | |
Testing Portions of the Multiple Regression Model | |
Coefficient of Partial Determination | |
Using Dummy-Variables and Interaction Terms in Regression Models | |
Interactions | |
Logistic Regression | |
Summary | |
Using Software for Multiple Regression | |
Multiple Regression Model Building | |
Using Statistics: Predicting Standby Hours for Unionized Artists | |
The Quadratic Regression Model | |
Finding the Regression Coefficients and Predicting Y | |
Testing for the Significance of the Quadratic Effect | |
Testing the Quadratic Effect | |
The Coefficient of Multiple Determination | |
Using Transformations in Regression Models | |
The Square Root Transformation | |
The Log Transformation | |
Influence Analysis | |
Collinearity | |
Model Building | |
The Stepwise Regression Approach to Model Building | |
The Best-Subsets Approach to Model Building | |
Model Validation | |
Pitfalls in Multiple Regression and Ethical Issues | |
Pitfalls in Multiple Regression | |
Ethical Issues | |
Summary | |
Using Software for Multiple Regression Model Building | |
Time-Series Forecasting and Index Numbers | |
Using Statistics: Forecasting Revenues for Three Companies | |
The Importance of Business Forecasting | |
Component Factors of the Classical Multiplicative Time-Series Model | |
Smoothing the Annual Time Series | |
Moving Averages | |
Exponential Smoothing | |
Least-Squares Trend Fitting and Forecasting | |
The Linear Trend Model | |
The Quadratic Trend Model | |
The Exponential Trend Model | |
The Holt-Winters Method for Trend-Fitting and Forecasting | |
Autoregressive Modeling for Trend Fitting and Forecasting | |
Choosing an Appropriate Forecasting Model | |
Performing a Residual Analysis | |
Measuring the Magnitude of the Residual Error through Squared or Absolute Differences | |
Principle of Parsimony | |
Time-Series Forecasting of Monthly or Quarterly Data | |
Least-Squares Forecasting with Monthly or Quarterly Data | |
Index Numbers | |
The Price Index | |
Aggregate Price Indexes | |
Weighted Aggregate Price Indexes | |
Paasche Price Index | |
Some Common Price Indexes | |
Pitfalls Concerning Time-Series Analysis | |
Summary | |
Using Software for Time-Series Forecasting and Index Numbers | |
Decision Making | |
Using Statistics: Selecting Stocks | |
Payoff Tables and Decision Trees | |
Criteria for Decision Making | |
Expected Monetary Value | |
Expected Opportunity Loss | |
Return-to-Risk Ratio | |
Decision Making with Sample Information | |
Utility | |
Summary | |
Using Software for Decision Making | |
Statistical Applications in Quality and Productivity Management | |
Total Quality Management | |
Six SigmaÂ“ Management | |
The Theory of Control Charts | |
Control Chart for the Proportion of Nonconforming Items The p Chart | |
The Red Bead Experiment: Understanding Process Variability | |
Control Chart for an Area of Opportunity the c Chart | |
Control Charts for the Range and the Mean | |
The R Chart: A Control Chart for Dispersion | |
The Chart | |
Process Capability | |
Customer Satisfaction and Specification Limits | |
Capability Indices | |
CPL, CPU, Cpk | |
Summary | |
Using Software for Control Charts | |
Answers to Self-Test Problems | |
Answers to Even-Numbered Problems | |
Appendices | |
Review of Arithmetic and Algebra | |
Summation Notation | |
Statistical Symbols and Greek Alphabet | |
CD-ROM Contents | |
Tables | |
Configuring and Customizing Microsoft Excel For Use With This Text | |
PHStat2 User's Guide | |
Index | |
CD-ROM Topics | |
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