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Statistics for managers using Microsoft Excel

Autore: David M Levine; et al
Editore: Upper Saddle River, N.J. : Pearson Prentice Hall, ©2008.
Edizione/Formato:   Libro : CD for computer   Computer File : English : 5th edVedi tutte le edizioni e i formati
Banca dati:WorldCat
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Tipo materiale: Risorsa internet
Tipo documento: Book, Computer File, Internet Resource
Tutti gli autori / Collaboratori: David M Levine; et al
ISBN: 9780132295451 0132295458 9780131579408 0131579401 0132295520 9780132295529
Numero OCLC: 77011575
Descrizione: xxvii, 858 p. : ill. (chiefly col.) ; 29 cm. + I CD-ROM (4 3/4 in.)
Dettagli: System requirements for accompanying disc: 200 MHz Pentium II Processor; 64 MB RAM; 57.1 MB free hard disk space; Windows ME/2000/NT/XP/Vista; Microsoft Excel.
Contenuti: Preface --
Chapter 1 --
Introduction and Data Collection --
1.1 Why Learn Statistics --
1.2 Statistics for Managers --
USING STATISTICS @ Good Tunes --
1.3 Basic Vocabulary of Statistics --
1.4 Data Collection --
1.5 Types of Variables --
Levels of Measurement and Measurement Scales --
1.6 Microsoft Excel Worksheets --
Worksheet Cells --
Designing Effective Worksheets --
Summary --
Key Terms --
Chapter Review Problems --
Introduction to the Web Cases --
Excel Companion to Chapter 1 --
E1.1 Preliminaries: Basic Computing Skills --
E1.2 Basic Workbook Operations --
E1.3 Worksheet Entries --
E1.4 Worksheet Formatting --
E1.5 Copy-and-Paste Operations --
E1.6 Add-ins: Making Things Easier for You --
Chapter 2 --
Presenting Data in Tables and Charts --
USING STATISTICS@ CHOICE IS YOURS --
2.1 Tables and Charts for Categorical Data --
The Summary Table --
The Bar Chart --
The Pie Chart --
The Pareto Diagram --
2.2 Organizing Numerical Data --
The Ordered Array --
The Stem-and-Leaf Display --
2.3 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) --
2.4 Cross Tabulations --
The Contingency Table --
The Side-by-Side Bar Chart --
2.5 Scatter Plots and Time-Series Plots --
The Scatter Plot --
The Time-Series Plot --
2.6 Misusing Graphs and Ethical Issues --
Summary --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 2 --
E2.1 Creating Summary Tables --
E2.2 Creating Charts --
E2.3 Creating Bar and Pie Charts from Summary Tables --
E2.4 Creating Pareto Diagrams from Summary Tables --
E2.5 Creating an Ordered Array --
E2.6 Creating Stem-and Leaf Displays --
E2.7 Creating Frequency Distributions and Histograms --
E2.8 Creating a Histogram from Summarized Data --
E2.9 Creating Polygons --
E2.10 Creating Contingency Tables --
E2.11 Creating Side-by-Side Charts --
E2.12 Creating Scatter Plots --
E2.13 Creating Time Series Plots --
3 Numerical Descriptive Measures --
Using Statistics@ Choice Is Yours --
3.1 Measures of Central Tendency --
The Mean --
The Median --
The Mode --
Quartiles --
The Geometric Mean --
3.2 Variation and Shape --
The Range --
The Interquartile Range --
The Variance and the Standard Deviation --
The Coefficient of Variation --
Z Scores --
Shape --
Visual Explorations: Exploring Descriptive Statistics --
Microsoft Excel Descriptive Statistics Output --
3.3 Numerical Descriptive Measures for a Population --
The Population Mean --
The Population Variance and Standard Deviation --
The Empirical Rule --
The Chebychev Rule --
3.4 Exploratory Data Analysis --
The Five-Number Summary --
The Box-and-Whisker Plot --
3.5 The Covariance and the Coefficient of Correlation --
The Covariance --
The Coefficient of Correlation --
3.6 Pitfalls in Numerical Descriptive Measures and Ethical Issues --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 3 --
E3.1 Computing Measures of Central Tendency, Variation, and Shape --
E3.2 Creating Dot Scale Diagrams --
E3.3 Computing Measures for a Population --
E3.4 Creating Box-and-Whisker Plots --
E3.5 Computing the Covariance --
E3.6 Computing the Correlation Coefficient --
4 Basic Probability --
Using Statistics@The Consumer Electronics Company --
4.1 Basic Probability Concepts --
Events and Sample Spaces --
Contingency Tables --
Simple (Marginal) Probability --
Joint Probability --
General Addition Rule --
4.2 Conditional Probability --
Computing Conditional Probabilities --
Decision Trees --
Statistical Independence --
Multiplication Rules --
Marginal Probability Using the General Multiplication Rule --
4.3 Bayes' Theorem --
4.4 Ethical Issues and Probability --
CD-ROM Topic 4.5 Counting Rules --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Web Case --
Excel Companion to Chapter 4 --
E4.1 Computing Basic Probabilities --
E4.2 Using Bayes' Theorem --
5 Some Important Discrete Probability Distributions --
Using Statistics@ Saxon Home Improvement --
5.1 The Probability Distribution for a Discrete Random Variable --
Expected Value of a Discrete Random Variable --
Variance and Standard Deviation of a Discrete Random Variable --
5.2 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 --
5.3 Binomial Distribution --
5.4 Poisson Distribution --
5.5 Hypergeometric Distribution --
5.6 (CD ROM Topic) Using the Poisson Distribution to Approximate the Binomial --
Distribution --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 5 --
E5.1 Computing the Expected Value of a Discrete Random Variable --
E5.2 Computing Portfolio Expected Return & Portfolio Risk --
E5.3 Computing Binomial Probabilities --
E5.4 Computing Poisson Probabilities --
E5.5 Computing Hypergeometric Probabilities --
E5.6 Creating Histograms for Discrete Probability Distributions --
6 The Normal Distribution and Other Continuous Distributions --
Using Statistics@OurCampus! --
6.1 Continuous Probability Distributions --
6.2 The Normal Distribution --
6.3 Evaluating Normality --
Comparing Data Characteristics to Theoretical Properties --
Constructing the Normal Probability Plot --
6.4 The Uniform Distribution --
6.5 The Exponential Distribution --
CD-ROM Topic 6.6 The Normal Approximation to the Binomial Distribution --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 6 --
E6.1 Computing Normal Probabilities --
E6.2 Creating Normal Probability Plots --
E6.3 Computing Exponential Probabilities --
7 Sampling and Sampling Distributions --
Using Statistics@Oxford Cereals --
7.1 Types of Survey Sampling Methods --
Simple Random Sample --
Systematic Sample --
Stratified Sample --
Cluster Sample --
7.2 Evaluating Survey Worthiness --
Survey Errors --
Ethical Issues --
7.3 Sampling Distributions --
7.4 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 --
7.5 Sampling Distribution of the Proportion --
7.6 (CD-ROM Topic) Sampling from Finite Populations --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 7 --
E7.1 Creating Simple Random Samples (without replacement) --
E7.2 Creating Simulated Sampling Distributions --
8 Confidence Interval Estimation --
Using Statistics@ SAXON HOME IMPROVEMENT --
8.1 Confidence Interval Estimation for the Mean (? Known) --
8.2 Confidence Interval Estimation for the Mean (? Unknown) --
Student's t Distribution --
Properties of the t Distribution --
The Concept of Degrees of Freedom --
The Confidence Interval Statement --
8.3 Confidence Interval Estimation for the Proportion --
8.4 Determining Sample Size --
Sample Size Determination for the Mean --
Sample Size Determination for the Proportion --
8.5 Applications of Confidence Interval Estimation in Auditing --
Estimating the Population Total Amount --
Difference Estimation --
One-Sided Confidence Interval Estimation of the Rate of Noncompliance with Internal Controls --
8.6 Confidence Interval Estimation and Ethical Issues --
8.7 CD-ROM Topic: Estimation and Sample Size Determination for Finite --
Populations --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
EXCEL COMPANION to Chapter 8 --
E8.1 Computing the Confidence Interval Estimate for the Mean (? known) --
E8.2 Computing the Confidence Interval Estimate for the Mean (? unknown) --
E8.3 Computing the Confidence Interval Estimate for the Proportion --
E8.4 Computing the Sample Size Needed for Estimating the Mean --
E8.5 Computing the Sample Size Needed for Estimating the Proportion --
E8.6 Computing the Confidence Interval Estimate for the Population Total --
E8.7 Computing the Confidence Interval Estimate for the Total Difference --
E8.8 Computing Finite Population Correction Factors --
9 Fundamentals of Hypothesis Testing: One-Sample Tests --
Using Statistics@ Oxford Cereals, Part II --
9.1 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 --
9.2 Z Test of Hypothesis for the Mean??? Known) --
The Critical Value Approach to Hypothesis Testing --
The p-Value Approach to Hypothesis Testing --
A Connection between Confidence Interval Estimation and Hypothesis --
Testing --
9.3 One-Tail Tests --
The Critical Value Approach --
The p-Value Approach --
9.4 t Test of Hypothesis for the Mean (? Unknown) --
The Critical Value Approach --
The p-Value Approach --
Checking Assumptions --
9.5 Z Test of Hypothesis for the Proportion --
The Critical Value Approach --
The p-Value Approach --
9.6 Potential Hypothesis-Testing Pitfalls and Ethical Issues --
9.7 CD-ROM Topic The Power of a Test --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 9. --
E9.1 Using the Z Test for the Mean (? known) --
E9.2 Using the t Test for the Mean (? unknown) --
E9.3 Using the Z Test for the Proportion --
10 Two-Sample Tests --
Using Statistics@BLK Foods --
10.1 Comparing the Means of Two Independent Populations --
Z Test for the Difference Between Two Means --
Pooled-Variance t Test for the Difference Between Two Means --
Confidence Interval Estimate for the Difference Between Two Means --
Separate-Variance t Test for the Difference Between Two Means --
10.2 Comparing the Means of Two Related Populations --
Paired t Test --
Confidence Interval Estimate for the Mean Difference --
10.3 Comparing Two Population Proportions --
Z Test for the Difference Between Two Proportions --
Confidence Interval Estimate for the Difference Between Two Proportions --
10.4 F Test for the Difference Between Two Variances --
Finding Lower-Tail Critical Values --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 10 --
Two-Sample Hypothesis Testing in Microsoft Excel --
E10.1 Using the Z Test for the Difference Between Two Means (Unsummarized Data) --
E10.2 Using the Z Test for the Difference Between Two Means (Summarized Data) --
E10.3 Using the Pooled-Variance t Test (Unsummarized Data) --
E10.4 Using the Pooled-Variance t Test (Summarized Data) --
E10.5 Using the Separate-Variance t Test for the Difference Between Two Means (Unsummarized Data) --
E10.6 Using the Paired t Test for the Difference Between Two Means (Unsummarized Data) --
E10.7 Using the Z Test for the Difference Between Two Proportions (Summarized Data) --
E10.8 Using the F Test for the Difference Between Two Variances (Unsummarized Data) --
E10.9 Using the F Test for the Difference Between Two Variances (Summarized Data) --
11 Analysis of Variance --
Using Statistics @ Perfect Parachutes --
11.1 The Completely Randomized Design: One-Way Analysis of Variance --
F Test for Differences Among More Than Two Means --
Multiple Comparisons: The Tukey-Kramer Procedure --
ANOVA Assumptions --
Levene's Test for Homogeneity of Variance --
11.2 The Factorial Design: Two-Way Analysis of Variance --
Testing for Factor and Interaction Effects --
Interpreting Interaction Effects --
Multiple Comparisons: The Tukey Procedure --
11.3 CD-ROM Topic The Randomized Block Design --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 11 --
E11.1 Using the F Test for Differences Among More Than Two Means --
E11.2 Using the Tukey-Kramer Procedure --
E11.3 Using the Levene Test for Homogeneity of Variance --
E11.4 Using The Two-Way ANOVA --
12 Chi-Square Tests and Nonparametric Tests --
Using Statistics@ T.C. Resort Properties --
12.1 Chi-Square Test for the Difference Between Two Proportions (Independent Samples) --
12.2 Chi-Square Test for Differences Among More than Two Proportions --
The Marascuilo Procedure --
12.3 Chi-Square Test of Independence --
12.4 McNemar Test for the Difference Between Two Proportions (Related Samples) --
12.5 Wilcoxon Rank Sum Test: Nonparametric Analysis for Two Independent Populations --
12.6 Kruskal-Wallis Rank Test: Nonparametric Analysis for the One-Way ANOVA --
12.7 CD-ROM Topic Chi-Square Test for a Variance or Standard Deviation --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 12 --
E12.1 Using the Chi-Square Test for the Difference Between Two Proportions --
E12.2 Using the Chi-Square Test for the Differences in More Than Two Proportions --
E12.3 Using the Chi-Square Test of Independence --
E12.4 Using the McNemar Test --
E12.5 Using the Wilcoxon Rank Sum Test --
E12.6 Using the Kruskal-Wallis Rank Test --
13 Simple Linear Regression --
Using Statistics@ Sunflowers Apparel --
13.1 Types of Regression Models --
13.2 Determining the Simple Linear Regression Equation --
The Least-Squares Method --
Visual Explorations: Exploring Simple Linear Regression Coefficients --
Predictions in Regression Analysis: Interpolation versus Extrapolation --
Computing the Y Intercept b0 and the Slope b1 --
13.3 Measures of Variation --
Computing the Sum of Squares --
The Coefficient of Determination --
Standard Error of the Estimate --
13.4 Assumptions --
13.5 Residual Analysis --
Evaluating the Assumptions --
13.6 Measuring Autocorrelation: The Durbin-Watson Statistic --
Residual Plots to Detect Autocorrelation --
The Durbin-Watson Statistic --
13.7 Inferences About the Slope and Correlation Coefficient --
t Test for the Slope --
F Test for the Slope --
Confidence Interval Estimate for the Slope (?1) --
t Test for the Correlation Coefficient --
13.8 Estimation of Mean Values and Prediction of Individual Values --
The Confidence Interval Estimate --
The Prediction Interval --
13.9 Pitfalls in Regression and Ethical Issues --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 13 --
E13.1 Performing Simple Linear Regression Analysis --
E13.2 Creating Scatter Diagrams and Adding a Prediction Line --
E13.3 Performing Residual Analyses --
E13.4 Computing the Durbin-Watson Statistic --
E13.5 Estimating the Mean of Y and Predicting Y Values --
E13.6 Example: Sunflowers Site Selection Data --
14 Introduction to Multiple Regression --
Using Statistics@ OMNIFOODS --
14.1 Developing the Multiple Regression Model --
Interpreting the Regression Coefficients --
Predicting the Dependent Variable Y --
14.2 R2, Adjusted R2, and the Overall F Test --
Coefficient of Multiple Determination --
Test for the Significance of the Overall Multiple Regression Model --
14.3 Residual Analysis for the Multiple Regression Model --
14.4 Inferences Concerning the Population Regression Coefficients --
Tests of Hypothesis --
Confidence Interval Estimation --
14.5 Testing Portions of the Multiple Regression Model --
Coefficients of Partial Determination --
14.6 Using Dummy Variables and Interaction Terms in Regression Models --
Interactions --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 14 --
E14.1 Creating Multiple Regression Models --
E14.2 Creating Multiple Regression Residual Plots --
E14.3 Computing the Confidence Interval Estimate of the Mean and Prediction --
Interval --
E14.4 Computing the Coefficients of Partial Determination --
E14.5 Creating Dummy Variables --
E14.6 Creating Interaction Terms. --
15 Multiple Regression Model Building --
USING STATISTICS@WTT-TV --
15.1 The Quadratic Regression Model --
Finding the Regression Coefficients and Predicting Y --
Testing for the Significance of the Quadratic Model --
Testing the Quadratic Effect --
The Coefficient of Multiple Determination --
15.2 Using Transformations in Regression Models --
The Square-Root Transformation --
The Log Transformation --
15.3 Collinearity --
15.4 Model Building --
The Stepwise Regression Approach to Model Building --
The Best-Subsets Approach to Model Building --
Model Validation --
15.5 Pitfalls in Multiple Regression and Ethical Issues --
Pitfalls in Multiple Regression --
Ethical Issues --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
The Mountain States Potato Company Case --
Web Case --
Excel Companion to Chapter 15 --
E15.1 Creating a Quadratic Term --
E15.2 Creating Transformations --
E15.3 Computing Variance Inflationary Factors --
E15.4 Using Stepwise Regression --
E15.5 Using Best-Subsets Regression --
16 Time-Series Forecasting and Index Numbers --
Using Statistics@ THE PRINCIPLED --
16.1 The Importance of Business Forecasting --
16.2 Component Factors of the Classical Multiplicative Time-Series Model --
16.3 Smoothing the Annual Time Series --
Moving Averages --
Exponential Smoothing --
16.4 Least-Squares Trend-Fitting and Forecasting --
The Linear Trend Model --
The Quadratic Trend Model --
The Exponential Trend Model --
Model Selection Using First, Second, and Percentage Differences --
16.5 Autoregressive Modeling for Trend-Fitting and Forecasting --
16.6 Choosing an Appropriate Forecasting Model --
Performing a Residual Analysis --
Measuring the Magnitude of the Residual Error through Squared or --
Absolute Differences --
Principle of Parsimony --
A Comparison of Four Forecasting Methods --
16.7 Time-Series Forecasting of Seasonal Data --
Least-Squares Forecasting with Monthly or Quarterly Data --
16.8 Index Numbers --
The Price Index --
Aggregate Price Indexes --
Weighted Aggregate Price Indexes --
Some Common Price Indexes --
16.9 Pitfalls Concerning Time-Series Forecasting --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Managing the Springville Herald --
Web Case --
Excel Companion to Chapter 16 --
E16.1 Computing Moving Averages --
E16.2 Creating Time-Series Plots --
E16.3 Creating Exponentially Smoothed Values --
E16.4 Creating Coded X Variables --
E16.5 Creating Quadratic and Exponential Terms --
E16.6 Using Least-Squares Linear Trend Fitting --
E16.7 Using Least-Squares Quadratic Trend Fitting --
E16.8 Using Least-Squares Exponential Trend Fitting --
E16.9 Creating Lagged Independent Variables --
E16.10 Creating First-Order Autoregressive Models --
E16.11 For Second-Order or Third-Order Autoregressive Models --
E16.12 Computing the Mean Absolute Deviation (MAD) --
E16.13 Creating Dummy Variables for Quarterly or Monthly Data --
E16.14 Calculating Index Numbers --
17 Decision Making --
Using Statistics@Reliable Fund --
17.1 Payoff Tables and Decision Trees --
17.2 Criteria for Decision Making --
Expected Monetary Value --
Expected Opportunity Loss --
Return-to-Risk Ratio --
17.3 Decision Making with Sample Information --
17.4 Utility --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
Web Case --
Excel Companion to Chapter 17 --
E17.1 Computing Opportunity Loss --
E17.2 Computing Expected Monetary Value --
18 Statistical Applications in Quality and Productivity Management --
Using Statistics@ BEACHCOMBER HOTEL --
18.1 Total Quality Management --
18.2 Six Sigma Management --
18.3 The Theory of Control Charts --
18.4 Control Chart for the Proportion-The p Chart --
18.5 The Red Bead Experiment: Understanding Process Variability --
18.6 Control Charts for the Range and the Mean --
The R Chart --
The Chart --
18.7 Process Capability --
Customer Satisfaction and Specification Limits --
Capability Indexes --
CPL, CPU, and Cpk --
Summary --
Key Equations --
Key Terms --
Chapter Review Problems --
The Harnswell Sewing Machine Company Case --
Managing the Springville Herald --
Excel Companion to Chapter 18 --
E18.1 Creating p Charts --
E18.2 Creating R and Charts --
Appendices --
A. Review of Arithmetic, Algebra, and Logarithms --
B. Summation Notation --
C. Statistical Symbols and Greek Alphabet --
D. CD-ROM Contents --
E. Tables --
F. Configuring Microsoft Excel and Installing PHStat --
Self-Test Solutions and Answers to Selected Even-Numbered Problems --
Index --
CD-ROM Topics (available as Adobe Reader .PDF files on the text CD) --
4.5 Counting Rules --
5.6 Using the Poisson Distribution to Approximate the Binomial Distribution --
6.6 The Normal Approximation to the Binomial Distribution --
7.6 Sampling from Finite Populations --
8.7 Estimation and Sample Size Determination for Finite Populations --
9.7 The Power of a Test --
11.3 The Randomized Block Design --
12.7 Chi-Square Test for a Variance or Standard Deviation.
Responsabilità: David M. Levine ... [et al.].
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schema:description"-- 15 Multiple Regression Model Building -- USING STATISTICS@WTT-TV -- 15.1 The Quadratic Regression Model -- Finding the Regression Coefficients and Predicting Y -- Testing for the Significance of the Quadratic Model -- Testing the Quadratic Effect -- The Coefficient of Multiple Determination -- 15.2 Using Transformations in Regression Models -- The Square-Root Transformation -- The Log Transformation -- 15.3 Collinearity -- 15.4 Model Building -- The Stepwise Regression Approach to Model Building -- The Best-Subsets Approach to Model Building -- Model Validation -- 15.5 Pitfalls in Multiple Regression and Ethical Issues -- Pitfalls in Multiple Regression -- Ethical Issues -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- The Mountain States Potato Company Case -- Web Case -- Excel Companion to Chapter 15 -- E15.1 Creating a Quadratic Term -- E15.2 Creating Transformations -- E15.3 Computing Variance Inflationary Factors -- E15.4 Using Stepwise Regression -- E15.5 Using Best-Subsets Regression -- 16 Time-Series Forecasting and Index Numbers -- Using Statistics@ THE PRINCIPLED -- 16.1 The Importance of Business Forecasting -- 16.2 Component Factors of the Classical Multiplicative Time-Series Model -- 16.3 Smoothing the Annual Time Series -- Moving Averages -- Exponential Smoothing -- 16.4 Least-Squares Trend-Fitting and Forecasting -- The Linear Trend Model -- The Quadratic Trend Model -- The Exponential Trend Model -- Model Selection Using First, Second, and Percentage Differences -- 16.5 Autoregressive Modeling for Trend-Fitting and Forecasting -- 16.6 Choosing an Appropriate Forecasting Model -- Performing a Residual Analysis -- Measuring the Magnitude of the Residual Error through Squared or -- Absolute Differences -- Principle of Parsimony -- A Comparison of Four Forecasting Methods -- 16.7 Time-Series Forecasting of Seasonal Data -- Least-Squares Forecasting with Monthly or Quarterly Data -- 16.8 Index Numbers -- The Price Index -- Aggregate Price Indexes -- Weighted Aggregate Price Indexes -- Some Common Price Indexes -- 16.9 Pitfalls Concerning Time-Series Forecasting -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 16 -- E16.1 Computing Moving Averages -- E16.2 Creating Time-Series Plots -- E16.3 Creating Exponentially Smoothed Values -- E16.4 Creating Coded X Variables -- E16.5 Creating Quadratic and Exponential Terms -- E16.6 Using Least-Squares Linear Trend Fitting -- E16.7 Using Least-Squares Quadratic Trend Fitting -- E16.8 Using Least-Squares Exponential Trend Fitting -- E16.9 Creating Lagged Independent Variables -- E16.10 Creating First-Order Autoregressive Models -- E16.11 For Second-Order or Third-Order Autoregressive Models -- E16.12 Computing the Mean Absolute Deviation (MAD) -- E16.13 Creating Dummy Variables for Quarterly or Monthly Data -- E16.14 Calculating Index Numbers -- 17 Decision Making -- Using Statistics@Reliable Fund -- 17.1 Payoff Tables and Decision Trees -- 17.2 Criteria for Decision Making -- Expected Monetary Value -- Expected Opportunity Loss -- Return-to-Risk Ratio -- 17.3 Decision Making with Sample Information -- 17.4 Utility -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Web Case -- Excel Companion to Chapter 17 -- E17.1 Computing Opportunity Loss -- E17.2 Computing Expected Monetary Value -- 18 Statistical Applications in Quality and Productivity Management -- Using Statistics@ BEACHCOMBER HOTEL -- 18.1 Total Quality Management -- 18.2 Six Sigma Management -- 18.3 The Theory of Control Charts -- 18.4 Control Chart for the Proportion-The p Chart -- 18.5 The Red Bead Experiment: Understanding Process Variability -- 18.6 Control Charts for the Range and the Mean -- The R Chart -- The Chart -- 18.7 Process Capability -- Customer Satisfaction and Specification Limits -- Capability Indexes -- CPL, CPU, and Cpk -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- The Harnswell Sewing Machine Company Case -- Managing the Springville Herald -- Excel Companion to Chapter 18 -- E18.1 Creating p Charts -- E18.2 Creating R and Charts -- Appendices -- A. Review of Arithmetic, Algebra, and Logarithms -- B. Summation Notation -- C. Statistical Symbols and Greek Alphabet -- D. CD-ROM Contents -- E. Tables -- F. Configuring Microsoft Excel and Installing PHStat -- Self-Test Solutions and Answers to Selected Even-Numbered Problems -- Index -- CD-ROM Topics (available as Adobe Reader .PDF files on the text CD) -- 4.5 Counting Rules -- 5.6 Using the Poisson Distribution to Approximate the Binomial Distribution -- 6.6 The Normal Approximation to the Binomial Distribution -- 7.6 Sampling from Finite Populations -- 8.7 Estimation and Sample Size Determination for Finite Populations -- 9.7 The Power of a Test -- 11.3 The Randomized Block Design -- 12.7 Chi-Square Test for a Variance or Standard Deviation."@en
schema:description"Preface -- Chapter 1 -- Introduction and Data Collection -- 1.1 Why Learn Statistics -- 1.2 Statistics for Managers -- USING STATISTICS @ Good Tunes -- 1.3 Basic Vocabulary of Statistics -- 1.4 Data Collection -- 1.5 Types of Variables -- Levels of Measurement and Measurement Scales -- 1.6 Microsoft Excel Worksheets -- Worksheet Cells -- Designing Effective Worksheets -- Summary -- Key Terms -- Chapter Review Problems -- Introduction to the Web Cases -- Excel Companion to Chapter 1 -- E1.1 Preliminaries: Basic Computing Skills -- E1.2 Basic Workbook Operations -- E1.3 Worksheet Entries -- E1.4 Worksheet Formatting -- E1.5 Copy-and-Paste Operations -- E1.6 Add-ins: Making Things Easier for You -- Chapter 2 -- Presenting Data in Tables and Charts -- USING STATISTICS@ CHOICE IS YOURS -- 2.1 Tables and Charts for Categorical Data -- The Summary Table -- The Bar Chart -- The Pie Chart -- The Pareto Diagram -- 2.2 Organizing Numerical Data -- The Ordered Array -- The Stem-and-Leaf Display -- 2.3 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) -- 2.4 Cross Tabulations -- The Contingency Table -- The Side-by-Side Bar Chart -- 2.5 Scatter Plots and Time-Series Plots -- The Scatter Plot -- The Time-Series Plot -- 2.6 Misusing Graphs and Ethical Issues -- Summary -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 2 -- E2.1 Creating Summary Tables -- E2.2 Creating Charts -- E2.3 Creating Bar and Pie Charts from Summary Tables -- E2.4 Creating Pareto Diagrams from Summary Tables -- E2.5 Creating an Ordered Array -- E2.6 Creating Stem-and Leaf Displays -- E2.7 Creating Frequency Distributions and Histograms -- E2.8 Creating a Histogram from Summarized Data -- E2.9 Creating Polygons -- E2.10 Creating Contingency Tables -- E2.11 Creating Side-by-Side Charts -- E2.12 Creating Scatter Plots -- E2.13 Creating Time Series Plots -- 3 Numerical Descriptive Measures -- Using Statistics@ Choice Is Yours -- 3.1 Measures of Central Tendency -- The Mean -- The Median -- The Mode -- Quartiles -- The Geometric Mean -- 3.2 Variation and Shape -- The Range -- The Interquartile Range -- The Variance and the Standard Deviation -- The Coefficient of Variation -- Z Scores -- Shape -- Visual Explorations: Exploring Descriptive Statistics -- Microsoft Excel Descriptive Statistics Output -- 3.3 Numerical Descriptive Measures for a Population -- The Population Mean -- The Population Variance and Standard Deviation -- The Empirical Rule -- The Chebychev Rule -- 3.4 Exploratory Data Analysis -- The Five-Number Summary -- The Box-and-Whisker Plot -- 3.5 The Covariance and the Coefficient of Correlation -- The Covariance -- The Coefficient of Correlation -- 3.6 Pitfalls in Numerical Descriptive Measures and Ethical Issues -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 3 -- E3.1 Computing Measures of Central Tendency, Variation, and Shape -- E3.2 Creating Dot Scale Diagrams -- E3.3 Computing Measures for a Population -- E3.4 Creating Box-and-Whisker Plots -- E3.5 Computing the Covariance -- E3.6 Computing the Correlation Coefficient -- 4 Basic Probability -- Using Statistics@The Consumer Electronics Company -- 4.1 Basic Probability Concepts -- Events and Sample Spaces -- Contingency Tables -- Simple (Marginal) Probability -- Joint Probability -- General Addition Rule -- 4.2 Conditional Probability -- Computing Conditional Probabilities -- Decision Trees -- Statistical Independence -- Multiplication Rules -- Marginal Probability Using the General Multiplication Rule -- 4.3 Bayes' Theorem -- 4.4 Ethical Issues and Probability -- CD-ROM Topic 4.5 Counting Rules -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Web Case -- Excel Companion to Chapter 4 -- E4.1 Computing Basic Probabilities -- E4.2 Using Bayes' Theorem -- 5 Some Important Discrete Probability Distributions -- Using Statistics@ Saxon Home Improvement -- 5.1 The Probability Distribution for a Discrete Random Variable -- Expected Value of a Discrete Random Variable -- Variance and Standard Deviation of a Discrete Random Variable -- 5.2 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 -- 5.3 Binomial Distribution -- 5.4 Poisson Distribution -- 5.5 Hypergeometric Distribution -- 5.6 (CD ROM Topic) Using the Poisson Distribution to Approximate the Binomial -- Distribution -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 5 -- E5.1 Computing the Expected Value of a Discrete Random Variable -- E5.2 Computing Portfolio Expected Return & Portfolio Risk -- E5.3 Computing Binomial Probabilities -- E5.4 Computing Poisson Probabilities -- E5.5 Computing Hypergeometric Probabilities -- E5.6 Creating Histograms for Discrete Probability Distributions -- 6 The Normal Distribution and Other Continuous Distributions -- Using Statistics@OurCampus! -- 6.1 Continuous Probability Distributions -- 6.2 The Normal Distribution -- 6.3 Evaluating Normality -- Comparing Data Characteristics to Theoretical Properties -- Constructing the Normal Probability Plot -- 6.4 The Uniform Distribution -- 6.5 The Exponential Distribution -- CD-ROM Topic 6.6 The Normal Approximation to the Binomial Distribution -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 6 -- E6.1 Computing Normal Probabilities -- E6.2 Creating Normal Probability Plots -- E6.3 Computing Exponential Probabilities -- 7 Sampling and Sampling Distributions -- Using Statistics@Oxford Cereals -- 7.1 Types of Survey Sampling Methods -- Simple Random Sample -- Systematic Sample -- Stratified Sample -- Cluster Sample -- 7.2 Evaluating Survey Worthiness -- Survey Errors -- Ethical Issues -- 7.3 Sampling Distributions -- 7.4 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 -- 7.5 Sampling Distribution of the Proportion -- 7.6 (CD-ROM Topic) Sampling from Finite Populations -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 7 -- E7.1 Creating Simple Random Samples (without replacement) -- E7.2 Creating Simulated Sampling Distributions -- 8 Confidence Interval Estimation -- Using Statistics@ SAXON HOME IMPROVEMENT -- 8.1 Confidence Interval Estimation for the Mean (? Known) -- 8.2 Confidence Interval Estimation for the Mean (? Unknown) -- Student's t Distribution -- Properties of the t Distribution -- The Concept of Degrees of Freedom -- The Confidence Interval Statement -- 8.3 Confidence Interval Estimation for the Proportion -- 8.4 Determining Sample Size -- Sample Size Determination for the Mean -- Sample Size Determination for the Proportion -- 8.5 Applications of Confidence Interval Estimation in Auditing -- Estimating the Population Total Amount -- Difference Estimation -- One-Sided Confidence Interval Estimation of the Rate of Noncompliance with Internal Controls -- 8.6 Confidence Interval Estimation and Ethical Issues -- 8.7 CD-ROM Topic: Estimation and Sample Size Determination for Finite -- Populations -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- EXCEL COMPANION to Chapter 8 -- E8.1 Computing the Confidence Interval Estimate for the Mean (? known) -- E8.2 Computing the Confidence Interval Estimate for the Mean (? unknown) -- E8.3 Computing the Confidence Interval Estimate for the Proportion -- E8.4 Computing the Sample Size Needed for Estimating the Mean -- E8.5 Computing the Sample Size Needed for Estimating the Proportion -- E8.6 Computing the Confidence Interval Estimate for the Population Total -- E8.7 Computing the Confidence Interval Estimate for the Total Difference -- E8.8 Computing Finite Population Correction Factors -- 9 Fundamentals of Hypothesis Testing: One-Sample Tests -- Using Statistics@ Oxford Cereals, Part II -- 9.1 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 -- 9.2 Z Test of Hypothesis for the Mean??? Known) -- The Critical Value Approach to Hypothesis Testing -- The p-Value Approach to Hypothesis Testing -- A Connection between Confidence Interval Estimation and Hypothesis -- Testing -- 9.3 One-Tail Tests -- The Critical Value Approach -- The p-Value Approach -- 9.4 t Test of Hypothesis for the Mean (? Unknown) -- The Critical Value Approach -- The p-Value Approach -- Checking Assumptions -- 9.5 Z Test of Hypothesis for the Proportion -- The Critical Value Approach -- The p-Value Approach -- 9.6 Potential Hypothesis-Testing Pitfalls and Ethical Issues -- 9.7 CD-ROM Topic The Power of a Test -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 9."@en
schema:description"-- E9.1 Using the Z Test for the Mean (? known) -- E9.2 Using the t Test for the Mean (? unknown) -- E9.3 Using the Z Test for the Proportion -- 10 Two-Sample Tests -- Using Statistics@BLK Foods -- 10.1 Comparing the Means of Two Independent Populations -- Z Test for the Difference Between Two Means -- Pooled-Variance t Test for the Difference Between Two Means -- Confidence Interval Estimate for the Difference Between Two Means -- Separate-Variance t Test for the Difference Between Two Means -- 10.2 Comparing the Means of Two Related Populations -- Paired t Test -- Confidence Interval Estimate for the Mean Difference -- 10.3 Comparing Two Population Proportions -- Z Test for the Difference Between Two Proportions -- Confidence Interval Estimate for the Difference Between Two Proportions -- 10.4 F Test for the Difference Between Two Variances -- Finding Lower-Tail Critical Values -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 10 -- Two-Sample Hypothesis Testing in Microsoft Excel -- E10.1 Using the Z Test for the Difference Between Two Means (Unsummarized Data) -- E10.2 Using the Z Test for the Difference Between Two Means (Summarized Data) -- E10.3 Using the Pooled-Variance t Test (Unsummarized Data) -- E10.4 Using the Pooled-Variance t Test (Summarized Data) -- E10.5 Using the Separate-Variance t Test for the Difference Between Two Means (Unsummarized Data) -- E10.6 Using the Paired t Test for the Difference Between Two Means (Unsummarized Data) -- E10.7 Using the Z Test for the Difference Between Two Proportions (Summarized Data) -- E10.8 Using the F Test for the Difference Between Two Variances (Unsummarized Data) -- E10.9 Using the F Test for the Difference Between Two Variances (Summarized Data) -- 11 Analysis of Variance -- Using Statistics @ Perfect Parachutes -- 11.1 The Completely Randomized Design: One-Way Analysis of Variance -- F Test for Differences Among More Than Two Means -- Multiple Comparisons: The Tukey-Kramer Procedure -- ANOVA Assumptions -- Levene's Test for Homogeneity of Variance -- 11.2 The Factorial Design: Two-Way Analysis of Variance -- Testing for Factor and Interaction Effects -- Interpreting Interaction Effects -- Multiple Comparisons: The Tukey Procedure -- 11.3 CD-ROM Topic The Randomized Block Design -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 11 -- E11.1 Using the F Test for Differences Among More Than Two Means -- E11.2 Using the Tukey-Kramer Procedure -- E11.3 Using the Levene Test for Homogeneity of Variance -- E11.4 Using The Two-Way ANOVA -- 12 Chi-Square Tests and Nonparametric Tests -- Using Statistics@ T.C. Resort Properties -- 12.1 Chi-Square Test for the Difference Between Two Proportions (Independent Samples) -- 12.2 Chi-Square Test for Differences Among More than Two Proportions -- The Marascuilo Procedure -- 12.3 Chi-Square Test of Independence -- 12.4 McNemar Test for the Difference Between Two Proportions (Related Samples) -- 12.5 Wilcoxon Rank Sum Test: Nonparametric Analysis for Two Independent Populations -- 12.6 Kruskal-Wallis Rank Test: Nonparametric Analysis for the One-Way ANOVA -- 12.7 CD-ROM Topic Chi-Square Test for a Variance or Standard Deviation -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 12 -- E12.1 Using the Chi-Square Test for the Difference Between Two Proportions -- E12.2 Using the Chi-Square Test for the Differences in More Than Two Proportions -- E12.3 Using the Chi-Square Test of Independence -- E12.4 Using the McNemar Test -- E12.5 Using the Wilcoxon Rank Sum Test -- E12.6 Using the Kruskal-Wallis Rank Test -- 13 Simple Linear Regression -- Using Statistics@ Sunflowers Apparel -- 13.1 Types of Regression Models -- 13.2 Determining the Simple Linear Regression Equation -- The Least-Squares Method -- Visual Explorations: Exploring Simple Linear Regression Coefficients -- Predictions in Regression Analysis: Interpolation versus Extrapolation -- Computing the Y Intercept b0 and the Slope b1 -- 13.3 Measures of Variation -- Computing the Sum of Squares -- The Coefficient of Determination -- Standard Error of the Estimate -- 13.4 Assumptions -- 13.5 Residual Analysis -- Evaluating the Assumptions -- 13.6 Measuring Autocorrelation: The Durbin-Watson Statistic -- Residual Plots to Detect Autocorrelation -- The Durbin-Watson Statistic -- 13.7 Inferences About the Slope and Correlation Coefficient -- t Test for the Slope -- F Test for the Slope -- Confidence Interval Estimate for the Slope (?1) -- t Test for the Correlation Coefficient -- 13.8 Estimation of Mean Values and Prediction of Individual Values -- The Confidence Interval Estimate -- The Prediction Interval -- 13.9 Pitfalls in Regression and Ethical Issues -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 13 -- E13.1 Performing Simple Linear Regression Analysis -- E13.2 Creating Scatter Diagrams and Adding a Prediction Line -- E13.3 Performing Residual Analyses -- E13.4 Computing the Durbin-Watson Statistic -- E13.5 Estimating the Mean of Y and Predicting Y Values -- E13.6 Example: Sunflowers Site Selection Data -- 14 Introduction to Multiple Regression -- Using Statistics@ OMNIFOODS -- 14.1 Developing the Multiple Regression Model -- Interpreting the Regression Coefficients -- Predicting the Dependent Variable Y -- 14.2 R2, Adjusted R2, and the Overall F Test -- Coefficient of Multiple Determination -- Test for the Significance of the Overall Multiple Regression Model -- 14.3 Residual Analysis for the Multiple Regression Model -- 14.4 Inferences Concerning the Population Regression Coefficients -- Tests of Hypothesis -- Confidence Interval Estimation -- 14.5 Testing Portions of the Multiple Regression Model -- Coefficients of Partial Determination -- 14.6 Using Dummy Variables and Interaction Terms in Regression Models -- Interactions -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 14 -- E14.1 Creating Multiple Regression Models -- E14.2 Creating Multiple Regression Residual Plots -- E14.3 Computing the Confidence Interval Estimate of the Mean and Prediction -- Interval -- E14.4 Computing the Coefficients of Partial Determination -- E14.5 Creating Dummy Variables -- E14.6 Creating Interaction Terms."@en
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