3 NUMERICAL DESCRIPTIVE MEASURES 71
Using Statistics: Evaluating the Performance of Mutual Funds 72
Measures of Central Tendency, Variation and Shape 72
The Mean 73
The Median 75
The Mode 76
Quartiles 77
The Geometric Mean 79
The Range 80
The Interquartile Range 81
The Variance and the Standard Deviation 82
The Coefficient of Variation 85
Z Scores 86
Shape 88
Visual Explorations: Exploring Descriptive Statistics 88
Microsoft Excel Descriptive Statistics Output 89
Minitab Descriptive Statistics Output 90
Numerical Descriptive Measures for a Population 94
The Population Mean 94
The Population Variance and Standard Deviation 95
The Empirical Rule 96
The Chebyshev Rule 97
Computing Numerical Descriptive Measures form a Frequency
Distribution 99
Exploratory Data Analysis 101
The Five-Number Summary 102
The Box-and-Whisker Plot 103
The Covariance and the Coefficient of Correlation 106
The Covariance 106
The Coefficient of Correlation 108
Pitfalls in Numerical Descriptive Measures and Ethical Issues 112
Ethical Issues 113
Summary 113
Key Formulas 114
Key Terms 114
Chapter Review Problems 115
Managing the Springville Herald 121
Web Case 121
A.3 Using Software for Descriptive Statistics 121
A3.1 Microsoft Excel 121
A3.2 Minitab 121
A3.3 (CD-ROM Topic) SPSS CD3-1
4 BASIC PROBABILITY 125
Using Statistics: The Consumer Electronics Company 126
Basic Probability Concepts 126
Events and Sample Spaces 128
Contingency Tables and Venn Diagrams 129
Simple (Marginal) Probability 129
Joint Probability 131
General Addition Rule 132
Conditional Probability 135
Computing Conditional Probabilities 135
Decision Trees 137
Statistical Independence 138
Multiplication Rules 140
Bayes’ Theorem 143
Counting Rules 147
Ethical Issues and Probability 150
Summary 151
Key Formulas 151
Key Terms 152
Chapter Review Problems 152
Web Case 154
A.4 Using Software for Basic Probability 155
A4.1 Microsoft Excel 155
5 SOME IMPRTANT DESCRETE PROBABILITY DISTRIBUTIONS 157
Using Statistics: The Accounting Information System of the Saxon Home
Improvement Company 158
5.1 The Probability Distribution for a Discrete Random Variable 158
Expected Value of a Discrete Random Variable 159
Variance and Standard Deviation of a Discrete Random Variable 160
5.2 Covariance and Its Application in Finance 162
The Covariance 162
The Expected Value, Variance, and Standard Deviation of the Sum of Two
Random Variables 163
Portfolio Expected Return and Portfolio Risk 164
5.3 Binomial Distribution 166
5.4 Poisson Distribution 175
5.5 Hypergeometric Distribution 179
The Mean 180
The Standard Deviation 180
5.6 CD-ROM Topic: Using the Poisson Distribution to Approximate the Binomial Distribution 182
Summary 182
Key Formulas 183
Key Terms 183
Chapter Review Problems 184
Managing the Springville Herald 187
Web Case 188
A.5 Using Software for Discrete Probability Distributions 188
A5.1 Microsoft Excel 188
A5.2 Minitab 189
6 THE NORMAL DISTRIBUTION AND OTHER CONTINUOUS DISTRIBUTIONS 191
Using Statistics: Download Time for a Web Site Homepage 192
6.1 Continuous Probability Distributions 192
6.2 The Normal Distribution 193
Visual Explorations: Exploring the Normal Distribution 202
6.3 Evaluating Normality 208
Evaluating the Properties 208
Constructing the Normal Probability Plot 209
6.4 The Uniform Distribution 213
6.5 The Exponential Distribution 215
6.6 The Normal Approximation to Binomial Distribution 218
Need for a Correction for Continuity Adjustment 218
Approximating the Binomial Distribution 218
Computing a Probability Approximation for an Individual Value 220
Summary 220
Key Formulas 221
Key Terms 221
Chapter Review Problems 221
Managing the Springville Herald 223
Web Case 224
A.6 Using Software for Continuous Probability Distributions 224
A6.1 Microsoft Excel 224
A6.2 Minitab 225
A6.3 (CD-ROM Topic) SPSS CD6-12
7 SAMPLING DISTRIBUTIONS 227
Using Statistics: Cereal-Fill Packaging Process 228
7.1 Sampling Distributions 228
7.2 Sampling Distribution of the Mean 229
The Unbiased Property of the Sample Mean 229
Standard Error of the Mean 230
Sampling from Normally Distributed Populations 232
Sampling from Nonnormally Distributed Populations-The Central Limit
Theorem 235
Visual Explorations: Exploring Sampling Distributions 237
7.3 Sampling Distribution of the Proportion 239
7.4 Types of Survey Sampling Methods 242
Simple Random Sample 243
Systematic Sample 245
Stratified Sample 246
Cluster Sample 246
7.5 Evaluating Survey Worthiness 248
Survey Errors 248
Ethical Issues 250
7.6 CD-ROM Topic: Sampling from Finite Populations 251
Summary 251
Key Formulas 251
Key Terms 252
Chapter Review Problems 252
Managing the Springville Herald 255
Web Case 255
A.7 Using Software for Sampling Distributions 256
A7.1 Microsoft Excel 256
A7.2 Minitab 256