**Errata and Notes on Multivariate Data Analysis, 5th
edition**

Errata:

Page |
Correction |

20 | Figure 1.2: in linear probability models chapter 4 should be chapter 5 |

28-29 | Table 1.3: reference to indep/dep is missing from Table |

42 | the 5th line from the bottom, should say "skewness in the opposite direction is indicated." |

72 | Figure 2.7: graph axes are reversed relative to SAS and to p81 |

74 | Figure 2.8(b): V1 distribution should be positively skewed |

81 | Figure 2.11: z should be |z| (twice) |

90 | Glossary entry for Reliability: remove "is intended to" and make "measure" plural |

171 | b_total should be b1_total |

189 | 3rd paragraph: Table 4.9 is on page 192, not 193. |

191 | Exhibit1: r_y,x1(x2) eqn should have 60- in the numerator |

191 | Exhibit1: second r_y,x1(x2) should be r_y,x2(x1) |

191 | Exhibit1: r_y,x2(x1) should refer to x_2 = .11^2, not x_1 |

225 | Line 13: +-2sqrt(n), should be +-2/sqrt(n) |

229 | 3rd line from bottom: value should be 0.08, not 0.2 |

244 | Expressions regarding Zjk should refer to Wij, not Wi |

193 | 8th line: VIF value should be 10, not .10 |

195 | Line 4: higher should be lower |

199 | First line in R Square section: expression should read (.7012 = .491) |

201 | 4th line from bottom: value should be 0.014, not 0.14 |

241 | Under "centroid" other uses of centroid (other than for Z scores) are also common. For example, the vectors of variable means for the original variables - when segregated into groups - are referred to as group centroids. The textbook prefers the name group mean as used in Table 5.1 on page 248. |

241 | Under "discriminant function," all W symbols should have a second
subscript j for the jth discriminant function. For example,
W_ij or W_ji. Also the intercepts should also be indexed with j. |

245 | in Figure 5.1 each figure should have the left-hand symmetrical area shaded also |

290 | Two corrections: |

6th line: correctly classified is 85.0 percent, not 86.4% | |

Press's Q calculations: should use 55 and 34 rather than 56 and 37. This results in new Q values of 41.7 and 19.6 | |

291 | Make the following changes in Table 5.10 |

The second (extra) line containing "Total Value Analysis" with values of 38, 4 and 34 should be deleted. | |

The percent of grouped cases correctly classified for the holdout sample is 85%. | |

335 | 4th line above T^2 equation: "N1+N2-2-1" should be "N1+N2-p-1" |

Notes:

29 | dummy coding for "specification buying" is unintuitively assigned |

99 | SAS does in fact supply partial correlation matrix |

292 | Add following footnote at bottom of Table 5.11 Note: Cases 82 and 64
are predicted to be in Group 0 rather than Group 1 since SPSS utilizes standardized
discriminant scores when separate variance estimates are used |

Chapter 5 | Note on classification process: Because separate variance estimates were empolyed in the two group example, SPSS utilizes standardized Z scores in classification. This results in two cases (#82 in the analysis sample and #64 in the holdout sample) to be classified as Group 0 (Specification Buying) whereas the simple cutting score approach would classify them as Group 1 (Total Value Analysis) |

The cutting score approach described in the text is a simplified description of the classification process and may not exactly replicate actual results in the instances of separate variance estimates, use of Fishers's linear discriminant functions for classification or other options. It does, however, accurately describe the basic process and will result in identical results in most situations. |