Lecture Business research methods (12e) Chapter 18: Measures of association

Lecture Business research methods (12e) Chapter 18: Measures of association. After studying this chapter you will be able to understand: How correlation analysis may be applied to study relationships between two or more variables; the uses, requirements, and interpretation of the product moment correlation coefficient; how predictions are made with regression analysis using the method of least squares to minimize errors in drawing a line of... Đề tài Hoàn thiện công tác quản trị nhân sự tại Công ty TNHH Mộc Khải Tuyên được nghiên cứu nhằm giúp công ty TNHH Mộc Khải Tuyên làm rõ được thực trạng công tác quản trị nhân sự trong công ty như thế nào từ đó đề ra các giải pháp giúp công ty hoàn thiện công tác quản trị nhân sự tốt hơn trong thời gian tới.

Chapter 18 MEASURES OF ASSOCIATION 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc All rights reserved c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 Learning Objectives Understand  How correlation analysis may be applied to study relationships between two or more variables  The uses, requirements, and interpretation of the product moment correlation coefficient  How predictions are made with regression analysis using the method of least squares to minimize errors in drawing a line of best fit 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-2 Learning Objectives Understand  How to test regression models for linearity and whether the equation is effective in fitting the data  Nonparametric measures of association and the alternatives they offer when key assumptions and requirements for parametric techniques cannot be met 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-3 Pull Quote “Consumer behavior with digital editions of magazines is very much like their behavior with print editions of magazines, and very much unlike their behavior with websites Readers typically swipe through tablet editions from front to back, for example, the same way they work their way through print editions They browse—taking in ads as they go—instead of jumping directly to specific articles the way web surfers do.” 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e   688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 Scott McDonald, senior vice-president for research and insights, Conde Nast 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-4 Measures of Association: Interval/Ratio Data Pearson correlation coefficient Correlation ratio (eta) Biserial For continuous linearly related variables For nonlinear data or relating a main effect to a continuous dependent variable One continuous and one dichotomous variable with an underlying normal distribution 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 Three variables; relating two with the third’s effect taken out 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 Partial correlation 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b Multiple correlation Three variables; relating one variable with two others 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 Bivariate linear regression Predicting one variable from another’s scores 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-5 Measures of Association: Ordinal Data Gamma Based on concordant-discordant pairs; proportional reduction in error (PRE) interpretation Kendall’s tau b P-Q based; adjustment for tied ranks Kendall’s tau c P-Q based; adjustment for table dimensions 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d Somers’s d P-Q based; asymmetrical extension of gamma 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b Product moment correlation for ranked data 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 Spearman’s rho 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-6 Measures of Association: Nominal Data Phi Chi-square based for 2*2 tables Cramer’s V CS based; adjustment when one table dimension >2 Contingency coefficient C CS based; flexible data and distribution assumptions Lambda PRE based interpretation 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e PRE based with table marginals emphasis 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d Goodman & Kruskal’s tau 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 Uncertainty coefficient Useful for multidimensional tables 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe Kappa Agreement measure f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-7 Researchers Search for Insights Burke, one of the world’s leading research companies, claims researchers add the most value to a project when they look beyond the raw numbers to the shades of gray…what the data really mean 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-8 Pearson’s Product Moment Correlation r Is there a relationship between X and Y? What is the magnitude of the relationship? 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 What is the direction of the relationship? df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-9 Connections and Disconnections “To truly understand consumers’ motives and actions, you must determine relationships between what they think and feel and what they actually do.” 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 David Singleton, vp of insights Zyman Marketing Group df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-10 Statistical Alternatives for Ordinal Measures 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-34 Calculation of Concordant (P), Discordant (Q), Tied (Tx,Ty), and Total Paired Observations: KeyDesign Example 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-35 KDL Data for Spearman’s Rho _ _ Rank By _ _ _ Applicant Panel x Psychologist y d d2 10 3.5 10.0 6.5 2.0 1.0 9.0 3.5 6.5 8.0 5.0 6.0 5.0 8.0 1.5 3.0 7.0 1.5 9.0 10.0 4.0 -2.5 5.0 -1.5 05 -2 2.0 2.0 -2.5 -2 1.0 6.25 25.00 2.52 0.25 4.00 4.00 4.00 6.25 4.00 _1.00_ 57.00 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-36 Key Terms 18-37  Artifact correlations  Bivariate correlation     analysis Bivariate normal distribution Chi-square-based measures Contingency coefficient C Cramer’s V  Phi  Coefficient of   determination (r2) Concordant Correlation matrix Discordant Error term Goodness of fit lambda 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78  69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e  688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857  203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8  05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-37 Key Terms 18-38 • Linearity • Pearson correlation • Method of least squares • Ordinal measures • • Gamma • Somers’s d • coefficient Prediction and confidence bands Proportional reduction in error (PRE) Regression analysis Regression coefficients 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 • Spearman’s rho 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e • tau b • • tau c • 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-38 Key Terms 18-39 • Intercept • Scatterplot • Slope • Simple prediction • Residual • tau 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-39 Chapter 18 ADDITIONAL DISCUSSION OPPORTUNITIES 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc All rights reserved c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 Snapshot: Oscars Does the Oscar have any measurable effect on movie viewership? Brief online survey via OmniPulse 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 Event hype only a small influence 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e Do women respond differently than men? d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-41 PicProfile: Constellation Wines Recession affected wine behavior Positioning research using focus groups Word sorts to reveal how Blackstone compared to other brands 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 ‘Masculine’ wasn’t threatening but a strength df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 Three ads by Amazon Advertising were tested; “Count on it” strongest 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-42 Snapshot: Environsell Does how you drive affect how you shop? Envirosell tracked shoppers’ behaviors 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 Observation studies 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e Brits and Aussies shop as they drive d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-43 Snapshot: Advanced Statistics “A risk score model was embedded in the daily transactions processing system to automatically determine how much cash each member can withdraw from an ATM or receive when making deposits.” 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-44 Pull Quote “The invalid assumption that correlation implies cause is probably among the two or three most serious and common errors of human reasoning.” 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 Stephen Jay Gould paleontologist and science writer df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-45 PulsePoint: Research Revelation 25 The percent of students using a credit card for college costs due to convenience 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-46 Chapter 18 MEASURES OF ASSOCIATION 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc All rights reserved c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 Photo Attributions Slide Source Courtesy of Burke Research Inc 41 ©Image Source, all rights reserved 42 Purestock/SuperStock 43 Purestock/SuperStock 44 Comstock Images/Getty Images 6b4090 276 f85e 7e79a2 7b4 f9d31306 2ff9828 5326 33d3 1409 b83a2 1eabae5 c78 69b235 50a5 c3c862be85 c992 c8a9 d31 cc7 8eb5 4cfda56e 5e9a28 26f8fcf74 565 4bb45 0f2 178 f0e02 f11 f3 f858 dd7 e448a6 231fe65db2a88 2044 c48 1c3 5a24df6 bc9 b0bcf6 4689 7071a2 696e7 f15 1a28a c446 11fbd8 db86 80ef6b9 8cc9b6 74dc1 df3a6 b9d39e60 7c3 09863 4a0f18e f8e90e f5 f54e 4fe0e e17fc36 91491 3481e 6e 688f0 1fc5a0 f29fe 01a1 f12bc58 e905 f3 c73b1d0e 18686 7c9 5c8 533 ccdd31 d8d 5ac1c03e9 7c0 9d11a 1e51fcb6a1e21 f59a 46c9796 d3ad0 16f5a324 85d6 6092 0b 85cbfd0 b14 f24 f71ee 04fbcfdd5 ed71 5fb4642 584d703 b0754 31c9d59 8785 e42 05bb4 6d10 f6a1 0a49fc87 4f4 ef7ff3 9e845fb 99d8 98157 b65 4c10 7b6 6e5e0 857 203076 c61 1f4 9f0 bca c3e09 e51 c452fb8 e3c6 26d5db4b01 0a9c3f7 752e7 b46e d9d2e cb4 2640a 78d3 1c7 88be 3195e d06 f227a 0a55e6 3c9 5c6 e5bdc8 493b45233 6241c8cf19 f4fe 18aca c143 58ed f87 5118 5b19 39fdd99 4c7 e0b6 5e9fca936 474 d600 f8f5a5205 f30 0647 0eaa75fb c03a6 cd1 296a7 baff2fde4fc88 c5d8 0e7e8 05c20 445 f057 6fba59ac8c4e 9bdf4e 2d37a 6e52e 4d1 fc0 d97e 52033 2486 b108 b 6ac85e 6b36 36b4 1df49 c267 c062 235bd48 0e9ed f9 dbd175b8eb7a 87444 0fa0 1dfe7 d7f7cf90a6 f92 74c81be 6be3 cbf7ee2 0416 0b53 5f5 7d8 c76 f1e6e 17e9 fe f3a8e f7a276 b2a0 4f9 2b17a 67137 b8a2 b5c136efb1e 7eaf7 81d1f4 316c593 d2c 0a2f44 210d1bfbcc3a7 35d5 1d13 f37 7b1 72d0 079b6dc0dfc35 e5ac1d8a5 f07 b5 ab5a5c1d67 622e0 44fd9c038a98 b3 f82 f5a071 7f5 9adefb04 4eeafe be3 c4c40e 54813e1 1a2e6a 6638e 29b2 0b7 c7e8a 1f7 92736 b1e8 c7ee ba292 7f7 2950 b4a90 b 87d180a 6f6 794a2 2d3 bb70a 4e2d2289aa8 df113fa 96d4 dd6 0d1 555e5 50f50086 24f6fb cc2 c3e2 d82a 7f4 2dc11d3 f7a8 4c9 d529 044 b7cfa91b4143 0b68 8aca f29 c5eac84c3f6 c86 c63 6c6 9f5ae 9f2 1f1 94c4b94 d1 c92e f3b8 8c4 e9b9a 3b5 cb2 8e b4a4b4 8b05 3489 bfa88 9d0 2057a9 3d2fb dd52 510 c0571 74e5 b5d0 9708 eb22 f03 18-48