## Basic Business Statistics: A CasebookPreface Statistics is seldom the most eagerly anticipated course of a business student. It typically has the reputation of being a boring, complicated, and confusing mix of mathematical formulas and computers. Our goal in writing this casebook and the companion volume (Business Analysis Using Regression) was to change that impression by showing how statistics yields insights and answers interesting business questions. Rather than dwell on underlying formulas, we show how to use statistics to answer questions. Each case study begins with a business question and concludes with an answer to that question. Formulas appear only as needed to address the questions, and we focus on the insights into the problem provided by the mathematics. The mathematics serves a purpose. The material in this casebook is organized into 11 "classes" of related case studies that develop a single, key idea of statistics. The analysis of data using statistics is seldom very straightforward, and each analysis has many nuances. Part of the appeal of statistics is this richness, this blending of substantive theories and mathematics. For newcomers, however, this blend is too rich, and they are easily overwhelmed and unable to sort out the important ideas from nuances. Although later cases in these notes suggest this complexity, we do not begin that way. |

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### Contents

Class 1 Overview and Foundations | 1 |

Class 2 Statistical Summaries of Data | 5 |

GMAT Scores | 9 |

Returns on General Motors Stock | 23 |

Skewness in Executive Compensation | 34 |

Class 3 Sources of Variation | 41 |

Variation by Industry in Executive Compensation | 45 |

Patterns in Early International Airline Passenger Data | 50 |

Hotel Satisfaction Survey | 114 |

Class 7 Making Decisions | 127 |

Selecting a Painting Process | 131 |

Effects of Reengineering a Food Processing Line | 141 |

Analysis of Time for Service Calls | 148 |

Class 8 Designing Tests for Better Comparisons | 155 |

TasteTest Comparison of Teas | 158 |

Pharmaceutical Sales Force Comparison | 163 |

Monitoring an Automotive Manufacturing Process | 55 |

Class 4 Standard Error | 65 |

Control Charts for Motor Shafts | 68 |

Control Chart Analysis of Car Trunk Seam Variation | 80 |

Analysis of Production of Computer Chips | 89 |

Class 5 Confidence Intervals | 93 |

Interval Estimates of the Process Mean Continued | 97 |

Purchases of Consumer Goods | 104 |

Class 6 Sampling | 107 |

Internet Use Surveys | 111 |

### Other editions - View all

Basic Business Statistics: A Casebook Dean P. Foster,Robert A. Stine,Richard P. Waterman No preview available - 2001 |

### Common terms and phrases

associated assumption boxplot central limit theorem chips Class column comparison confidence interval control charts control limits correlation Covariance data set DaysStay density estimate dependence Dev Std Err difference empirical rule example executive compensation factor formula Graph graphical groups histogram hypothesis test idea important independent indicates industry investment Kernel Key Application Mean Std Dev measure median menu method minimum 0.0 Minitab Moments Mean motor shaft mutual funds normal distribution normal model null hypothesis observations obtain outliers output p-value paired Penney population mean portfolio Prob probability process mean proportion Quantiles maximum 100.0 question random regression analysis relative changes risk risk-free Salary sales force sample mean scatterplot shaft diameters short selling shows skewed spreadsheet standard error Stat Std Dev Std Std Err Mean Std Error subset survey T-bills t-Test target trend two-sample variable variance weights zero