Dealer Satisfaction North America Scale 0 2010 2011 2012 2013 2014 Scale 1 1 0 1 1 2 Scale 2 0 0 1 2 3 2 2 1 6 5 Scale 3 Scale 4 Scale 5 Sample 14 22 11 50 14 20 14 50 8 34 15 60 12 34 45 100 15 44 56 125 Dealer Satification - North America 2010 2011 2012 2013 2014 2010 60 50 40 30 20 10 0 Scale 0 Scale 1 Scale 2 Dealer Satification - North America Scale 3 Scale 4 Scale 5 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2 2011 Scale 0 2013 2014 15 5 3 44 12 1 1 0 1 2012 2 34 14 1 2 1 0 Scale 1 34 8 6 20 14 2 Scale 2 56 22 Scale 3 Scale 4 45 15 14 11 Scale 5 South America Scale 0 2010 2011 2012 2013 2014 Scale 1 0 0 0 0 1 Scale 2 0 0 0 1 1 Scale 3 0 0 1 1 2 Scale 4 2 2 4 3 4 Scale 5 6 6 11 12 22 2 2 14 33 60 Sample 10 10 30 50 90 Dealer Satification - South America 2010 2011 2012 2013 2014 2010 70 60 50 40 30 20 10 0 Scale 0 Scale 1 Scale 2 Dealer Satification - South America Scale 3 Scale 4 Scale 5 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2011 2012 2013 2014 4 1 22 2 60 3 12 1 4 1 11 1 2 33 0 Scale 1 0 Scale 2 6 6 Scale 3 Scale 4 14 2 2 Scale 5 17 8 2 0 Scale 0 2 4 1 21 6 Europe Scale 0 2010 2011 2012 2013 2014 Scale 1 0 0 0 0 0 Scale 2 0 0 0 0 0 Scale 3 1 1 1 1 1 Scale 4 3 2 2 2 4 Scale 5 7 8 15 21 17 4 4 7 6 8 Sample 15 15 25 30 30 Dealer Satification - Europe Dealer Satification - Europe 2010 2011 2012 2013 100% 90% 2014 25 20 1 80% 60% 70% 1 50% 15 1 1 10 1 3 Scale 2 15 2 Scale 3 30% 20% 10% 5 0 2 40% 0% Scale 0 Scale 1 Scale 2 Scale 3 Scale 4 0 Scale 0 0 Scale 1 2010 Scale 5 2011 2012 2013 8 7 4 7 4 Scale 4 Scale 5 2014 Pacific Rim Scale 0 2010 2011 2012 2013 2014 Scale 1 0 0 0 0 0 Scale 2 0 0 0 0 0 Scale 3 1 1 1 0 1 Scale 4 2 1 1 2 2 Scale 5 2 3 3 5 7 Sample 0 0 1 3 2 5 5 6 10 12 Dealer Satification - Pacific Rim 2010 2011 2012 2013 2014 2010 8 7 6 5 4 3 2 1 0 China Scale 0 2012 2013 2014 Scale 1 0 0 0 Scale 2 0 0 0 Scale 3 0 1 1 Scale 4 1 4 5 Scale 5 0 2 8 Sample 0 0 2 1 7 16 Scale 0 Scale 1 Scale 2 Scale 3 Dealer Satification - Pacific Rim Scale 4 Scale 5 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2011 2012 1 2013 2 0 1 1 0 Scale 1 7 2 2 1 1 1 0 Scale 0 2014 2 Scale 2 Scale 3 5 3 3 3 2 Scale 4 1 0 Scale 5 Complaints Month World NA SA Eur Pac Jan-10 169 102 12 52 Feb-10 187 115 13 55 Mar-10 210 128 15 61 Apr-10 226 136 16 67 May-10 232 137 17 73 Jun-10 261 151 19 82 Jul-10 245 140 18 80 Aug-10 223 128 16 76 Sep-10 195 103 15 73 Oct-10 174 96 14 62 Nov-10 154 84 11 59 Dec-10 163 99 9 54 Jan-11 195 123 10 59 Feb-11 221 141 13 62 Mar-11 240 152 16 66 Apr-11 264 163 20 70 May-11 283 178 22 75 Jun-11 296 170 28 86 Jul-11 269 153 25 81 Aug-11 256 146 23 79 Sep-11 231 131 20 73 Oct-11 214 125 16 68 Nov-11 201 118 13 66 Dec-11 171 96 11 61 Jan-12 200 112 15 66 Feb-12 216 117 18 71 Mar-12 234 126 20 76 Apr-12 253 138 23 79 May-12 282 152 26 85 Jun-12 305 163 30 91 Jul-12 296 156 28 89 Aug-12 279 148 26 86 Sep-12 266 143 24 82 Oct-12 243 131 21 76 Nov-12 232 128 18 73 Dec-12 203 107 15 70 Jan-13 216 110 19 74 Feb-13 239 123 23 79 Mar-13 266 138 26 83 Apr-13 284 150 30 88 May-13 315 169 33 91 Jun-13 340 181 37 95 Jul-13 319 169 34 92 Aug-13 304 160 32 90 Sep-13 277 141 29 87 Oct-13 250 123 26 83 Nov-13 228 112 24 77 Dec-13 213 105 23 74 Jan-14 240 121 26 80 Feb-14 251 126 28 82 Mar-14 281 148 31 85 Apr-14 298 155 35 89 May-14 322 168 39 95 Jun-14 350 183 43 98 Jul-14 330 170 41 95 Aug-14 311 158 38 93 Sep-14 289 149 33 89 Oct-14 265 136 30 85 Nov-14 239 121 26 80 Dec-14 219 108 23 76 China 3 4 6 7 5 9 7 3 4 2 0 1 3 5 6 11 8 12 10 8 7 5 4 3 4 6 9 11 14 15 18 15 13 12 10 7 8 10 13 11 15 19 17 15 14 12 10 7 8 10 12 13 12 15 14 13 11 8 7 7 Complaints World NA SA Eur Pac China May-12 Dec-12 Jul-13 400 350 300 250 nUMBER OF cOMPLAINTS 200 150 100 50 0 Jan-10 Aug-10 Mar-11 Oct-11 mONTHS 3 4 3 2 5 6 5 4 4 3 3 4 5 4 6 5 7 8 7 7 6 6 5 4 5 5 5 6 8 11 10 9 7 6 5 5 Feb-14 Sep-14 On-Time Delivery Number of deliveries Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Jul-11 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 1086 1101 1116 1216 1183 1176 1198 1205 1223 1209 1198 1243 1220 1241 1237 1258 1262 1227 1243 1281 1272 1295 1298 1318 1281 1320 1352 1336 1291 1342 1352 1377 1385 1356 1362 1349 1386 1358 1371 1362 1350 1381 1392 1371 1402 1384 1399 1369 1401 1388 1395 1412 1403 1415 1426 1431 1445 1425 1413 1456 Number On Time 1069 1080 1089 1199 1168 1160 1181 1189 1210 1194 1180 1223 1201 1224 1217 1242 1246 1212 1227 1264 1254 1278 1281 1296 1264 1304 1334 1320 1276 1326 1337 1360 1368 1338 1346 1333 1371 1342 1356 1348 1338 1366 1378 1359 1387 1370 1377 1357 1390 1376 1385 1401 1392 1402 1415 1420 1426 1414 1403 1427 Percent 98.4% 98.1% 97.6% 98.6% 98.7% 98.6% 98.6% 98.7% 98.9% 98.8% 98.5% 98.4% 98.4% 98.6% 98.4% 98.7% 98.7% 98.8% 98.7% 98.7% 98.6% 98.7% 98.7% 98.3% 98.7% 98.8% 98.7% 98.8% 98.8% 98.8% 98.9% 98.8% 98.8% 98.7% 98.8% 98.8% 98.9% 98.8% 98.9% 99.0% 99.1% 98.9% 99.0% 99.1% 98.9% 99.0% 98.4% 99.1% 99.2% 99.1% 99.3% 99.2% 99.2% 99.1% 99.2% 99.2% 98.7% 99.2% 99.3% 98.0% On-Time Deliveries Number of deliveries Number On Time 1600 1400 1200 Number of on-time deliveries 1000 800 600 400 200 0 Jan-10 Jul-10 Jan-11 Jul-11 Jan-12 Jul-12 Jan-13 Jul-13 Jan-14 Jan-13 Oct-13 Jul-14 MONTHS Percent 99.5% 99.0% Percentage of On-Time Deliveries 98.5% 98.0% 97.5% 97.0% 96.5% Jan-10 Oct-10 Months Jul-11 Apr-12 Jul-14 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 A B C D E Defects After Delivery Defects per million items received from suppliers January February March April May June July August September October November December 2010 812 810 813 823 832 848 837 831 827 838 826 819 2011 828 832 847 839 832 840 849 857 839 842 828 816 2012 824 836 818 825 804 812 806 798 804 713 705 686 2013 682 695 692 686 673 681 696 688 671 645 617 603 F 2014 571 575 547 542 532 496 472 460 441 445 438 436 G H I J K L M N O P Defects 2010 DEFECTS 2011 2012 2013 2014 900 800 700 600 500 400 300 200 100 0 month Defects January July February August March September April October May November June December 900 800 700 600 500 400 300 200 100 0 2010 2011 2012 2013 2014 Q Response times to customer service calls Q1 2013 Q2 2013 Q3 2013 Q4 2013 Q1 2014 Q2 2014 Q3 2014 Q4 2014 4.36 4.33 3.71 4.44 2.75 3.45 1.67 2.55 5.42 4.73 2.52 4.07 3.24 1.95 2.58 2.30 5.50 1.63 2.69 5.11 4.35 2.77 3.47 1.04 2.79 4.21 3.47 3.49 5.58 1.83 3.12 1.59 5.55 6.89 5.12 4.69 2.89 3.72 1.00 3.11 3.65 0.92 1.00 6.36 5.09 4.59 5.40 4.05 8.02 5.27 3.44 8.26 2.33 1.17 3.90 3.38 4.00 0.90 6.04 1.91 1.69 1.46 4.49 1.26 3.34 3.85 2.53 8.93 3.88 1.90 2.06 0.90 4.92 5.00 2.39 6.85 3.39 2.95 4.49 2.31 3.55 3.52 3.26 5.69 5.14 4.69 3.57 2.71 3.52 5.20 4.68 3.05 0.98 3.34 3.41 1.65 1.25 5.13 3.59 5.91 2.34 3.59 3.31 3.58 2.18 5.29 1.07 1.00 2.80 4.03 2.79 2.96 4.35 1.00 2.86 1.82 3.06 2.39 2.09 3.78 2.46 2.18 4.44 3.74 2.40 1.63 4.28 2.87 2.07 4.55 4.87 6.11 1.59 2.40 4.47 0.90 2.90 2.13 6.76 4.78 3.05 4.44 1.94 4.87 2.58 5.24 2.84 4.13 1.50 4.96 3.90 3.11 5.50 4.08 1.25 7.17 5.58 4.41 3.32 0.90 2.47 4.04 3.43 5.70 3.11 3.40 2.20 3.52 4.24 5.09 2.98 1.00 1.08 3.15 3.52 3.18 1.88 7.66 4.65 3.40 3.63 4.87 2.31 0.90 4.25 4.65 2.66 2.04 1.86 3.97 1.00 1.35 5.08 0.90 4.99 4.37 1.90 3.85 5.90 1.62 4.40 2.01 3.76 2.47 6.07 2.81 1.09 1.87 1.64 1.34 3.12 3.20 1.00 1.76 4.60 1.03 6.40 8.05 2.12 5.83 1.00 5.58 3.52 2.31 3.68 4.91 4.32 3.94 1.19 4.92 4.14 1.99 3.92 5.06 3.61 2.47 3.79 2.63 4.13 3.97 4.13 3.26 4.02 3.89 5.86 3.27 2.43 1.00 3.34 4.26 2.63 6.88 0.90 2.86 2.34 3.51 3.28 1.70 4.47 1.71 2.24 3.83 2.53 2.41 3.24 2.30 4.18 6.39 0.90 1.79 4.14 2.47 3.25 5.35 4.73 6.57 3.87 2.70 2.65 4.02 5.20 2.33 2.65 4.18 2.46 3.61 3.21 2.03 5.28 3.67 2.36 8.82 3.84 0.90 3.85 3.62 4.33 4.73 3.64 3.35 2.43 3.38 2.20 4.12 4.64 1.05 5.62 5.50 1.54 4.38 4.57 1.40 2.65 2.67 0.90 6.51 0.90 2.87 2.99 2.49 3.42 4.16 6.40 0.90 3.69 2.11 4.19 2.67 3.97 0.90 3.21 2.87 1.73 2.86 3.03 4.33 1.26 3.51 3.55 7.45 3.52 3.12 1.90 1.95 6.16 5.95 5.93 3.49 2.23 1.86 2.09 2.70 6.40 2.05 5.52 3.03 5.35 2.41 1.03 1.76 1.00 8.21 4.96 7.46 5.11 2.98 2.95 2.64 3.63 2.52 4.85 4.84 6.46 0.90 7.42 4.49 5.34 3.99 5.57 2.88 5.61 1.01 3.79 1.62 3.74 2.59 4.82 0.95 3.63 4.56 2.48 1.10 5.63 1.34 3.18 3.05 3.87 5.67 2.71 4.50 Q1 2013 Q2 2013 9.00 9.00 8.00 8.00 7.00 7.00 6.00 6.00 5.00 5.00 4.00 4.00 3.00 3.00 2.00 2.00 1.00 1.00 0.00 0.00 Q3 2013 Q4 2013 8.00 10.00 7.00 9.00 8.00 6.00 7.00 5.00 6.00 4.00 5.00 4.00 3.00 3.00 2.00 2.00 1.00 1.00 0.00 0.00 Q1 2014 Q2 2014 7.00 6.00 6.00 5.00 5.00 4.00 4.00 3.00 3.00 2.00 2.00 1.00 1.00 0.00 0.00 Q4 2014 Q3 2014 8.00 7.00 6.00 5.00 6.00 5.00 4.00 3.00 4.00 3.00 2.00 2.00 1.00 0.00 1.00 0.00 Unit Shipping Cost Plant Customer Singapore Toronto Toronto Toronto Toronto Toronto Toronto Toronto Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Shanghai Mexico City Mexico City Mexico City Mexico City Mexico City Mexico City Mexico City Melbourne Melbourne Melbourne Melbourne Melbourne Melbourne Melbourne London London London London London London London Caracas Caracas Caracas Caracas Caracas Caracas Caracas Atlanta Atlanta Atlanta Atlanta Atlanta Atlanta Atlanta Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Singapore Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Singapore Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Singapore Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Singapore Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Singapore Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Singapore Birmingham Frankfurt Mumbai Kansas City Auckland Santiago Existing Plants Kansas City Santiago Proposed Plants Auckland Birmingham Frankfurt Mumbai Singapore Mowers Tractors Existing Plants Customer Mowers Tractors Existing Mowers $1.31 $1.31 $1.54 $1.00 $1.49 $1.82 $1.76 $1.90 $1.26 $1.86 First Quartile Second Quartile Third Quartile Fourth Quartile $1.58 $2.14 Existing Tractors $1.72 $1.49 $1.32 $1.22 $1.58 $1.47 $1.36 $1.49 $2.34 $1.80 $1.76 $1.58 $2.13 $2.03 $1.79 $2.13 First Quartile Second Quartile Third Quartile Fourth Quartile $1.71 $1.34 $1.52 $1.67 $1.36 $2.03 $1.78 $1.87 $2.14 $1.79 Kansas City Santiago Kansas City Santiago Kansas City $1.86 $2.19 Santiago $1.49 $1.44 $1.60 $1.65 $1.21 $1.58 $1.18 $1.47 $1.72 $2.13 $1.78 $2.15 $2.32 $1.47 $2.13 $1.63 $2.03 $2.09 Kansas City Santiago Kansas City Santiago Kansas City Santiago Kansas City Santiago Atlanta Atlanta Caracas Caracas London London Melbourne Melbourne Mexico City Mexico City Shanghai Shanghai Toronto Toronto $1.29 $1.79 Proposed Plants Customer Mowers Tractors Proposed Mowers $1.54 $1.56 $1.32 $1.50 $1.22 $2.04 $2.22 $1.76 $2.07 $1.58 Auckland $1.74 $1.02 $1.42 $1.57 $1.73 $2.26 $1.25 $1.70 $2.23 $2.35 First Quartile Second Quartile Third Quartile Fourth Quartile $1.43 $1.70 $1.54 $1.98 Proposed Tractors $1.52 $1.73 $1.38 $1.72 $0.91 $1.49 $1.88 $1.47 $1.37 $1.44 $1.49 $1.98 $1.58 $1.50 $1.37 $1.59 $1.61 $1.54 $1.54 $1.00 $1.73 $1.02 $1.42 $1.57 $1.31 $1.74 $1.31 $2.06 $2.28 $1.63 $2.34 $1.17 $1.80 $2.68 $1.77 $1.64 $1.82 $1.86 $2.60 $2.14 $2.01 $1.86 $1.88 $2.08 $1.90 $1.98 $1.26 $2.35 $1.25 $1.70 $2.23 $1.82 $2.26 $1.76 Atlanta Atlanta Atlanta Atlanta Atlanta Caracas Caracas Caracas Caracas Caracas London London London London London Melbourne Melbourne Melbourne Melbourne Melbourne Mexico City Mexico City Mexico City Mexico City Mexico City Shanghai Shanghai Shanghai Shanghai Shanghai Toronto Toronto Toronto Toronto Toronto $1.37 $1.59 $1.61 $1.50 $1.98 $1.47 $1.37 $1.44 $1.88 $0.91 $1.52 $1.73 $1.38 $1.43 $1.50 $1.29 $1.54 $1.56 $1.72 $1.18 $1.60 $1.65 $1.21 $1.44 $1.86 $1.34 $1.52 $1.67 $1.71 $1.86 $1.88 $2.08 $2.01 $2.60 $1.77 $1.64 $1.82 $2.68 $1.17 $2.06 $2.28 $1.63 $1.70 $2.07 $1.79 $2.04 $2.22 $2.09 $1.63 $2.15 $2.32 $1.47 $1.78 $2.19 $1.78 $1.87 $2.14 $2.03 First Quartile Second Quartile Third Quartile Fourth Quartile Birmingham Frankfurt Mumbai Singapore Auckland Birmingham Frankfurt Mumbai Singapore Auckland Birmingham Frankfurt Mumbai Singapore Auckland Birmingham Frankfurt Mumbai Singapore Auckland Birmingham Frankfurt Mumbai Singapore Auckland Birmingham Frankfurt Mumbai Singapore Auckland Birmingham Frankfurt Mumbai Singapore 1.31 1.48 1.53 1.72 1.77 1.84 2.11 2.34 1.40 1.52 1.66 1.98 1.78 2.01 2.17 2.68 2014 Customer Survey Region NA NA NA NA NA NA NA NA NA NA Quality 4 4 4 5 5 5 5 5 4 4 Ease of Use Price 1 4 5 4 4 5 4 5 4 5 Service 3 4 4 4 5 3 4 4 4 4 Cross Tabulation: 4 5 3 4 4 5 2 5 5 5 NA 4 5 1 5 5 4 5 5 5 5 4 4 4 4 5 5 5 5 5 4 5 5 5 4 4 5 5 5 5 5 4 5 5 5 5 4 5 4 5 4 4 5 4 4 3 5 3 4 5 5 4 4 1 4 5 4 3 5 4 5 5 3 4 4 5 4 3 4 3 2 2 2 4 5 2 3 2 4 4 2 5 5 4 5 3 1 3 4 2 4 4 4 3 4 3 1 4 3 4 5 5 5 5 4 4 4 4 5 3 5 5 3 4 4 5 5 4 5 4 4 4 4 5 5 3 4 5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 5 3 5 5 5 5 5 5 5 5 5 5 4 5 5 5 4 5 4 5 5 5 5 4 4 5 5 5 5 5 5 5 4 4 4 5 5 4 4 4 4 4 5 4 3 4 5 5 4 4 5 5 5 4 4 4 4 4 4 4 5 4 4 3 5 3 2 4 3 4 4 4 1 5 3 4 5 4 5 4 4 5 5 5 3 4 5 5 4 4 3 5 4 4 5 4 4 4 4 5 4 4 4 5 4 5 4 5 5 4 5 5 4 5 4 4 5 4 2 5 5 4 5 4 5 4 2 5 NA NA NA NA NA NA NA NA NA NA NA NA 5 5 4 3 5 4 3 1 4 5 4 5 4 4 5 5 5 4 2 4 5 5 5 5 5 1 3 2 4 3 4 3 3 4 5 4 5 5 5 5 4 5 5 4 5 4 5 5 Average - Ease of Use 3.8 4.1 4.6 4.4 4.28 4.395 Average - Price 4.1 4.3333333333 4.27 3.9 3.92 4.165 Number of Responses 3.50 3.00 Data Column J Column K Column L 2.50 0.50 0.00 Response Frequency 120 100 80 60 40 20 0 NA SA EUR PAC CHINA Region Quality: Number of Responses Survey Scale Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Total 2 2 16 75 105 200 Quality - Number of Responses 120 100 80 60 40 20 0 Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Survey Scale Ease of Use: Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Total 4.00 1.00 100 50 30 10 10 200 Survey Scale 4.50 1.50 NA SA EUR PAC CHINA TOTAL Number of responses 2.6 3.8666666667 4.31 4.3 4.24 4.14 5.00 2.00 Region Response Frequency Average - Service 3 3.9 3.71 4.1 3.5 3.67 Frequency Distribution: 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Data Average - Quality Region China Eur NA Pac SA Total Result Number of Responses 3 4 17 109 67 200 Easy to Use - Numbe rof Responses Region China Eur NA Pac SA NA NA NA NA NA NA NA NA NA NA NA NA NA NA SA SA SA SA SA SA 5 4 5 5 5 5 4 5 4 5 4 5 4 4 5 5 5 4 5 4 5 2 4 4 5 5 5 5 4 5 5 5 5 5 4 4 4 2 4 5 4 4 5 5 4 5 5 4 5 3 2 5 4 5 3 2 5 4 4 2 4 5 4 4 3 5 3 5 5 4 4 4 3 4 5 4 5 5 5 5 SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA 5 4 4 4 5 3 5 5 4 4 1 5 4 4 5 4 4 3 5 4 4 4 4 4 5 4 5 5 4 4 5 5 4 5 4 4 4 3 4 4 4 4 5 4 4 4 4 4 4 3 4 4 5 1 5 4 4 4 5 5 4 4 4 4 4 3 4 2 3 5 3 2 3 3 3 2 4 5 2 5 4 4 4 4 5 4 4 4 3 4 4 4 2 4 4 4 4 5 3 4 4 5 4 5 4 5 4 4 4 5 4 5 3 5 4 1 5 5 4 5 4 5 3 4 4 5 5 4 SA SA SA SA SA SA SA SA SA SA SA SA Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur 5 3 4 4 5 4 5 5 5 3 4 4 4 4 3 3 4 5 5 4 3 3 4 5 5 5 3 4 4 5 4 3 4 5 5 4 4 5 2 5 4 4 4 3 4 4 3 3 4 4 4 4 3 5 4 4 4 4 5 5 5 4 5 4 4 3 5 4 5 5 4 5 5 4 5 3 5 3 4 4 4 5 1 4 5 2 3 4 5 4 4 3 1 4 5 4 5 1 5 5 5 5 4 3 5 5 4 4 4 4 4 4 4 3 4 3 4 2 4 3 4 5 4 4 5 4 3 3 5 5 4 4 4 4 3 3 2 4 3 5 5 1 4 4 3 4 5 4 5 4 5 4 5 4 4 2 4 5 4 4 3 4 4 3 120 100 80 Number of Responses 60 40 20 0 Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Survey Scale Price: Number of Responses Survey Scale Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Total 9 21 40 87 43 200 Price - Number of Responses Number of Responses 100 90 80 70 60 50 40 30 20 10 0 Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Survey Scale Service: Number of Responses Survey Scale Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Total 3 8 25 86 78 200 Service - Number of Responses Number of Responses 100 90 80 70 60 50 40 30 20 10 0 Scale 1 Scale 2 Scale 3 Scale 4 Scale 5 Survey Scale Quartiles: Quality First Quartile Second Quartile Third Quartile Fourth Quartile Easy to Use 4 5 5 5 Price 4 4 5 5 Service 3 4 4 5 4 4 5 5 Eur Pac Pac Pac Pac Pac Pac Pac Pac Pac Pac China China China China China China China China China China 5 5 5 4 4 5 4 5 4 3 5 5 5 4 4 4 4 4 3 3 2 4 4 5 4 3 4 4 5 2 4 4 5 5 4 4 4 4 4 4 4 3 1 4 5 4 4 5 4 4 3 4 4 4 4 3 3 3 3 3 3 2 2 5 5 5 4 4 4 4 5 3 4 5 4 3 3 3 2 3 2 3 2 1 Chapter 4 Summary 4a: Mean Satisfaction Ratings & Standard Deviations for Dealer Satisfaction & End-User Satisfaction Dealer Satisfaction Mean Satisfaction Ratings Year / Region 2010 2011 2012 2013 2014 Standard Deviations of Satisfaction Ratings North America South America 3.78 3.92 3.97 4.11 4.11 4.00 4.00 4.27 4.50 4.50 Europe 3.93 4.00 4.12 4.07 4.07 Pacific Rim Year / Region China 3.20 3.40 3.67 4.10 3.83 3.00 3.14 3.69 Satisfaction in North America and South America rose from 2010 - 2013, and were flat in 2014. Europe peaked in 2012, and has fallen off slightly but remained steady in 2013/2014. The Pacific Rim rose through 2013 but has fallen off in 2014, while China has steadily increased since measurement was started in 2012. However, China still remains low comparatively. North America 2010 2011 2012 2013 2014 South America 0.97 0.85 0.94 1.07 1.09 Europe 0.67 0.67 0.83 0.86 0.91 Pacific Rim 0.88 0.85 0.73 0.64 0.74 China 0.84 0.89 1.03 N/A (sample size is 1) 0.74 0.69 0.83 0.79 The standard deviation in North America is relatively higher than in the other regions, indicating a greater spread in satisfaction ratings. Europe had the least deviation for a market with five years of data. End-User Satisfaction Mean Satisfaction Ratings Year / Region 2010 2011 2012 2013 2014 Standard Deviations of Satisfaction Ratings North America South America 3.98 4.04 4.04 4.17 4.22 4.00 3.95 3.99 4.00 4.02 Europe 3.97 3.96 3.90 4.07 4.07 Pacific Rim Year / Region China 3.92 3.95 4.00 4.06 4.07 3.78 3.86 4.12 Satisfaction in North America and Pacifc Rim has steadly risen over the five year period, and has remained realively flat in South America (slight improvement in 2014 vs. 2010) after expeeriencing a slight drop in 2011. Europe has increased to a lesser extent, and satisfaction in China has grown considerably since 2012. North America 2010 2011 2012 2013 2014 South America 1.10 1.04 1.06 0.96 0.95 Europe 1.05 1.10 0.99 0.97 0.97 Pacific Rim 1.04 1.06 0.99 0.96 0.83 China 1.13 1.06 1.03 N/A (sample size is 1) 0.94 1.07 0.87 0.77 South America deviations are the highest, indicating relatively more deviation from the mean in that region. Standard deviations are low in China. 4b: Mean Satisfaction Ratings & Standard Deviations for Dealer Satisfaction & End-User Satisfaction Quality Descriptive Statistics Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Ease of Use North America South America Europe Pacific Rim China 4.6 4.28 4.1 4.4 3.8 0.0651338947 0.110804111 0.1542501327 0.2211083194 0.2905932629 5 4 4 4.5 4 5 4 4 5 4 0.6513389473 0.7835033829 0.844862772 0.6992058988 0.9189365835 0.4242424242 0.613877551 0.7137931034 0.4888888889 0.8444444444 8.4272940399 4.9038829531 -0.3857732969 -0.1461038961 0.3962208152 -2.2828060147 -1.6072789705 -0.5660811264 -0.7801057548 -0.6013816284 4 4 3 2 3 1 1 2 3 2 5 5 5 5 5 460 214 123 44 38 100 50 30 10 10 Price Descriptive Statistics Mean Standard Error Median Mode Standard Devia Sample Varian Kurtosis Skewness Range Minimum Maximum Sum Count North America 4.27 0.0827006284 4 4 0.8270062841 0.6839393939 4.0158528777 -1.6366410443 4 1 5 427 100 South America 3.92 0.102379845 4 4 0.7239348262 0.5240816327 5.215213212 -1.5583105328 4 1 5 196 50 Europe 4.3333333333 0.1206622848 4 4 0.6608945523 0.4367816092 -0.6197071626 -0.4835096175 2 3 5 130 30 Pacific Rim 3.9 0.2768874621 4 4 0.8755950358 0.7666666667 1.8309478801 -1.0179412987 3 2 5 39 10 China 4.1 0.1795054936 4 4 0.5676462122 0.3222222222 1.498216409 0.0911203789 2 3 5 41 10 Service Descriptive Statistics Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count North America South America 3.71 0.1103666982 4 4 1.1036669824 1.2180808081 0.0138293006 -0.7793320956 4 1 5 371 100 3.5 0.1491472358 4 4 1.0546302186 1.112244898 -0.2815885188 -0.5980617034 4 1 5 175 50 Europe 3.9 0.1997124369 4 4 1.0938700673 1.1965517241 1.7080553621 -1.3142590667 4 1 5 117 30 Pacific Rim 4.1 0.1795054936 4 4 0.5676462122 0.3222222222 1.498216409 0.0911203789 2 3 5 41 10 China 3 0.2108185107 3 3 0.6666666667 0.4444444444 0.0803571429 0 2 2 4 30 10 Descriptive Statistics Mean Standard Error Median Mode Standard Devia Sample Varian Kurtosis Skewness Range Minimum Maximum Sum Count North America 4.31 0.074799395 4 5 0.7479939502 0.5594949495 1.0069137551 -1.0218961189 3 2 5 431 100 South America 4.24 0.116268514 4 4 0.8221425469 0.6759183673 3.4449652149 -1.3977558925 4 1 5 212 50 Europe 3.8666666667 0.1840373109 4 4 1.008013866 1.016091954 1.0933729566 -1.0151356855 4 1 5 116 30 Pacific Rim 4.3 0.2134374746 4 4 0.6749485577 0.4555555556 -0.282994816 -0.4336373839 2 3 5 43 10 China 2.6 0.2666666667 3 3 0.8432740427 0.7111111111 0.3703962054 -0.389108384 3 1 4 26 10 North America scores the highest in terms of quality, which was the region's highest scoring attribute. China had the lowest score in both Price and Service, and Europe is the only other territory with service scores below 4. The other territories appear to have a good rating on service. Overall Quality and Ease of use had good scores. Skewness is negative in all regions in all categories, except for Ease of use in China and the Price in Pacific Rim and China. 4c: Response Times Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Q1 2013 3.92 0.2095858101 3.8287067395 #N/A 1.4819954754 2.1963105892 0.0934185299 0.2232050003 7.0191382648 1 8.0191382648 195.797721365 50 Q2 2013 3.73 0.2709605451 4.0126144298 0.9 1.9159803885 3.6709808491 -0.3371273008 0.3238393214 7.3124891818 0.9 8.2124891818 186.25304851 50 Q3 2013 3.75 0.1978337086 3.6015919753 #N/A 1.3988955692 1.9569088134 -0.3629801746 0.0052102172 5.8562134567 0.9 6.7562134567 187.368190699 50 Q4 2013 4.45 0.2996076242 4.1544100883 1 2.1185458274 4.4882364228 -0.6905091163 0.2241857096 8.0296140787 0.9 8.9296140787 222.646527952 50 Q1 2014 3.09 0.2241866698 2.9721918359 0.9 1.5852391443 2.5129831447 -0.8081827897 0.4147159439 5.5554624679 0.9 6.4554624679 154.416974147 50 Q2 2014 3.11 0.1736917252 3.0501939444 0.9 1.2281859671 1.5084407698 -0.6719582392 0.0894306989 4.766074875 0.9 5.666074875 155.68763839 50 Q3 2014 3.20 0.180933972 3.164010146 1 1.279396385 1.636855109 1.300136981 0.652158538 6.419242032 1 7.419242032 160.1353723 50 Q4 2014 2.53 0.159924593 2.4774047079 0.9 1.1308376422 1.2787937731 -0.9831071927 0.2326587601 3.9724379854 0.9 4.8724379854 126.3914791599 50 (1.93) -43% Mean Response T ime 5.00 4.50 4.45 4.00 3.92 3.50 3.75 3.73 3.20 3.11 3.09 3.00 2.53 2.50 2.00 1.50 1.00 0.50 Q1 2013 Q2 2013 Q3 2013 Q4 2013 Q1 2014 Q2 2014 Q3 2014 Q4 2014 After peaking in Q4 2013, the Mean Response Time has steadily improved. Q4-2014 results of 2.53 are 1.93 better (43%) than the peak in Q4-2013. Q4-2013 also showed the hightest deviation, and Q4-2014 has shown the lowest. This indicates that the time to respond in Q4-2014 was not only the lowest, it was also was the most cosistently low. Response times are positively skewed and relatively symetrical, except for Q3 2014 which was more positively skewed. Response times are relatively flat with a wide degree of dispersion. 4d: Defects After Delivery Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count 2010 826.33 3.36 826.50 #N/A 11.63 135.33 (0.58) 0.22 38.00 810.00 848.00 9,916.00 12.00 2011 837.42 3.18 839.00 828.00 11.02 121.54 0.25 (0.14) 41.00 816.00 857.00 10,049.00 12.00 2012 785.92 15.14 805.00 804.00 52.44 2,749.72 (0.21) (1.21) 150.00 686.00 836.00 9,431.00 12.00 2013 669.08 8.94 681.50 #N/A 30.97 959.36 0.81 (1.39) 93.00 603.00 696.00 8,029.00 12.00 2014 496.25 15.65 484.00 #N/A 54.22 2,940.02 (1.75) 0.27 139.00 436.00 575.00 5,955.00 12.00 Variance (341.17) Var % Mean Defects After Delivery -39.9% 900.00 CAGR 800.00 -16.0% 700.00 600.00 500.00 400.00 300.00 200.00 100.00 2010 2011 2012 2013 After a slight increase from 2010 to 2011, the number of defects after delivery have steadily improved. 2014 of 496.25 results are 341.17 better than the peak in 2011, resulting in an improvement of 39.9% (average 16.0% per year). The standard deviation spiked in 2012, dropped in 2013, and spiked again in 2014. The distribution of defects was moderately skewed in 2010, 2011 and 2014, however showed a high degree of skewness in 2012 and 2013. 4e: Defects After Delivery Monthly Mower Sales Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Coefficient of Variation (CV) Industry Mower Sales NA 7,542.33 227.32 7,870.00 9,050.00 1,760.84 3,100,563.95 (1.24) (0.12) 6,020.00 4,350.00 10,370.00 452,540.00 60.00 SA 282.33 6.11 280.00 250.00 47.31 2,238.53 (0.29) 0.18 210.00 180.00 390.00 16,940.00 60.00 Europe 1,149.00 48.70 1,260.00 1,590.00 377.25 142,317.63 (0.85) (0.53) 1,350.00 300.00 1,650.00 68,940.00 60.00 Pacific 172.50 4.81 170.00 150.00 37.26 1,388.56 (1.19) 0.04 140.00 100.00 240.00 10,350.00 60.00 World 9,148.05 267.30 9,390.00 7,020.00 2,070.47 4,286,845.17 (1.19) (0.19) 6,930.00 5,350.00 12,280.00 548,883.00 60.00 23.35 16.76 32.83 21.60 22.63 Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Coefficient of Variation (CV The Coefficient of Variation in monthly mower sales for PLE is higher than the industry in all regions, althoug the variances are relativly small. The differences for entire popution for PLE and the worlrd are nearly identical. The skewness is relatively symetrical in all markets for both PLE and the industry, except for Europe with shows some moderate negative skewness. Variance Monthly Tractor Sales NA 72,580.89 2,159.85 75,883.02 60,000.00 16,730.09 279,896,046.40 (1.25) (0.15) 58,083.46 42,596.15 100,679.61 4,354,853.21 60.00 SA 675.84 13.44 654.15 625.00 104.14 10,844.55 (0.71) 0.42 424.18 461.54 885.71 40,550.44 60.00 Europe 21,120.05 860.52 23,831.24 29,444.44 6,665.53 44,429,314.58 (0.84) (0.60) 23,589.29 6,976.74 30,566.04 1,267,203.30 60.00 Pacific 1,628.23 42.72 1,552.54 1,214.95 330.88 109,484.59 (1.33) 0.06 1,136.82 1,045.00 2,181.82 97,693.66 60.00 World 96,004.17 2,816.73 97,955.18 #N/A 21,818.27 476,036,996.56 (1.14) (0.28) 75,786.03 53,981.68 129,767.72 5,760,250.07 60.00 23.05 15.41 31.56 20.32 22.73 0.30 1.35 1.27 1.28 (0.09) NA 7,726.27 SA 2,092.91 Europe 6,436.15 Pacific 1,322.73 China 1,069.89 Industry Tractor Sales Mean NA 1,075.03 SA 598.35 Europe 647.97 Pacific 272.18 China 46.65 World 2,640.18 Mean World 18,647.94 2014 Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Coefficient of Variation (CV) 75.71 835.00 570.00 586.42 343,888.03 (0.13) 1.01 2,130.00 360.00 2,490.00 64,502.00 60.00 30.37 605.00 280.00 235.26 55,347.93 (1.27) 0.00 752.00 250.00 1,002.00 35,901.00 60.00 12.19 647.50 680.00 94.45 8,920.30 (0.38) 0.40 408.00 480.00 888.00 38,878.00 60.00 5.01 270.00 290.00 38.84 1,508.53 (0.47) (0.09) 160.00 190.00 350.00 16,331.00 60.00 6.74 23.00 52.18 2,722.60 (1.25) 0.65 139.00 139.00 2,799.00 60.00 105.01 2,408.00 2,324.00 813.43 661,670.29 (0.65) 0.66 2,884.00 1,592.00 4,476.00 158,411.00 60.00 54.55 39.32 14.58 14.27 111.85 30.81 The Coefficient of Variation in monthly tractor sales for PLE are relatively higher than the industry in every territory, except for the Pacific Rim. This negative variation, however, is small. North America and China show large differences in their CV's. PLE South America shows perfect skewness (0). Correllation between Monthly Mower Sales & Industry Mower Sales: Correlation coefficient NA SA Europe Pacific World 0.9957982986 0.7571161785 0.9792084866 0.9901593969 0.9904798545 There is a strong positive linear relationship between monthly mower sales and industry mower sales in all territories except for South America, which shows a more moderate positive linear relationship. This indicates that changes in sales volume for industry are also felt at PLE. Correllation between Monthly Tractor Sales & Industry Tractor Sales: Correlation coefficient NA SA Europe Pacific China World 0.893424452 0.9990170468 0.9186482192 0.9803292025 0.9962614931 0.9602767915 There is a strong positive linear relationship between monthly tractor sales and industry tractor sales in all territories, with North America and Europe being slighly less than the other markets. The correlcation in South America is near perfect. Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count 293.86 7,559.52 #N/A 2,276.22 5,181,157.98 (0.18) 0.58 9,546.42 3,913.04 13,459.46 463,576.10 60.00 96.85 2,176.35 1,056.60 750.18 562,777.20 (1.24) (0.06) 2,412.39 977.44 3,389.83 125,574.48 60.00 107.71 6,318.27 6,666.67 834.30 696,057.28 (0.46) 0.47 3,330.45 5,050.51 8,380.95 386,168.98 60.00 24.98 1,298.20 1,126.76 193.53 37,454.24 (0.63) 0.23 758.31 974.36 1,732.67 79,363.62 60.00 117.10 588.74 315.00 907.06 822,763.75 (1.30) 0.68 2,375.06 278.00 2,653.06 64,193.13 60.00 467.76 17,747.65 #N/A 3,623.22 13,127,728.46 (0.59) 0.60 13,657.27 13,716.25 27,373.52 1,118,876.30 60.00 Coefficient of Variation (CV 29.46 35.84 12.96 14.63 84.78 19.43 Variance 25.09 3.47 1.61 (0.36) 27.07 11.38 Dealer Satisfaction Survey Scale: North America 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 0 1 2 3 4 1 0 1 1 2 0 0 1 2 3 2 2 1 6 5 14 14 8 12 15 22 20 34 34 44 11 14 15 45 56 50 50 60 100 125 0 0 0 0 1 0 0 0 1 1 0 0 1 1 2 2 2 4 3 4 6 6 11 12 22 2 2 14 33 60 NORTH AMERICA 5 Sample Size 10 10 30 50 90 Ratings (x) 2010 Totals Ratings (x) 2010 2011 2012 2013 2014 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 3 2 2 2 4 7 8 15 21 17 4 4 7 6 8 15 15 25 30 30 f*x 3.780 0.975 2011 Totals 4 42 80 70 196 f*(x-mean)^2 7.37 11.85 0.13 16.33 35.68 Mean Sample Std Dev 1 2 3 4 5 Europe Frequency (f) ### ### 14 20 14 50 4 42 88 55 189 f*(x-mean)^2 14.29 6.34 8.52 1.06 16.37 46.58 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 ### 14 22 11 50 SOUTH AMERICA f*x Ratings (x) Totals Ratings (x) 3.920 0.853 f*x 4.000 0.667 Totals 6 24 10 40 f*(x-mean)^2 2.00 2.00 4.00 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 6 2 10 6 24 10 40 f*(x-mean)^2 2.00 2.00 4.00 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 6 2 10 EUROPE f*x Ratings (x) Totals Ratings (x) 4.000 0.667 f*x 3.933 0.884 Totals 2 6 32 20 60 f*(x-mean)^2 4.00 2.00 4.00 10.00 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 2 8 4 15 2 9 28 20 59 f*(x-mean)^2 3.74 2.61 0.03 4.55 10.93 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 ### 7 4 15 f*x 4.000 0.845 Pacific Rim 2010 2011 2012 2013 2014 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 2 1 1 2 2 2 3 3 5 7 0 0 1 3 2 5 5 6 10 12 2012 2013 2014 0 0 0 0 0 0 0 1 1 1 4 5 0 2 8 0 0 2 1 7 16 Ratings (x) China 2012 Totals Ratings (x) f*x 3.967 0.938 2013 Totals Ratings (x) 1 2 3 4 5 2014 Totals Frequency (f) 2 3 5 15 44 56 125 2 12 36 136 225 411 f*(x-mean)^2 16.89 19.34 26.71 14.79 0.41 35.64 113.79 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 6 12 34 45 100 1 2 24 136 75 238 f*(x-mean)^2 15.73 8.80 3.87 7.48 0.04 16.02 51.93 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 ### 1 8 34 15 60 f*x Ratings (x) Totals 4.110 1.072 f*x 3 10 45 176 280 514 f*(x-mean)^2 33.82 29.05 22.30 18.55 0.55 44.16 148.43 Mean Sample Std Dev 4.112 1.094 Ratings (x) f*x 4.267 0.828 Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) 1 ### ### 4 22 60 90 1 2 9 48 165 225 f*(x-mean)^2 12.25 6.25 6.75 3.00 8.25 36.50 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### ### 1 ### 12 33 50 2 12 44 70 128 f*(x-mean)^2 5.14 6.42 0.78 7.53 19.87 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 4 11 14 30 f*x Ratings (x) Totals 4.500 0.863 f*x 1 4 12 88 300 405 f*(x-mean)^2 20.25 12.25 12.50 9.00 5.50 15.00 74.50 Mean Sample Std Dev 4.500 0.915 Ratings (x) f*x 4.120 0.726 Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### 1 4 17 8 30 2 6 84 30 122 f*(x-mean)^2 4.27 2.28 0.09 5.23 11.87 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 2 21 6 30 2 6 60 35 103 f*(x-mean)^2 4.49 2.51 0.22 5.42 12.64 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 2 15 7 25 f*x 4.067 0.640 f*x 2 12 68 40 122 f*(x-mean)^2 4.27 4.55 0.08 6.97 15.87 Mean Sample Std Dev 4.067 0.740 PACIFIC RIM Ratings (x) Totals Ratings (x) f*x 3.200 0.837 Totals Ratings (x) f*x Totals Ratings (x) f*x 2 3 12 5 22 f*(x-mean)^2 2.78 0.44 0.33 1.78 5.33 Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### 1 2 7 2 12 1 2 3 4 5 Totals Frequency (f) ### - f*x 6 20 15 41 f*(x-mean)^2 2.42 0.05 2.43 4.90 Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### - 2 6 28 10 46 f*(x-mean)^2 3.36 1.39 0.19 2.72 7.67 Mean Sample Std Dev 3.833 0.835 - f*x Mean Sample Std Dev Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### 1 1 f*x 3 3 f*(x-mean)^2 f*(x-mean)^2 f*(x-mean)^2 - Mean 3.000 Sample Std Dev N/A (sample size is 1) 4.100 0.738 f*x f*x Mean Sample Std Dev 3.667 1.033 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 5 3 10 Ratings (x) 3.400 0.894 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 1 3 1 6 2 3 12 17 f*(x-mean)^2 1.96 0.16 1.08 3.20 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 1 3 5 2 6 8 16 f*(x-mean)^2 1.44 0.08 1.28 2.80 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 2 2 5 CHINA Ratings (x) Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### 1 5 8 2 16 2 12 8 22 f*(x-mean)^2 1.31 0.08 1.47 2.86 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 1 4 2 7 f*x 3.143 0.690 f*x 2 15 32 10 59 f*(x-mean)^2 2.85 2.36 0.78 3.45 9.44 Mean Sample Std Dev 3.688 0.793 End-User Satisfaction Sample North America 2010 2011 2012 2013 2014 0 1 2 3 4 1 1 1 0 0 3 2 2 2 2 6 4 5 4 3 15 18 17 15 15 37 35 34 33 31 NORTH AMERICA 5 Size 38 40 41 46 49 100 100 100 100 Ratings (x) 2 3 2 2 2 5 6 6 5 5 18 17 19 20 19 36 36 37 37 37 38 37 36 36 37 100 100 100 100 100 Totals Ratings (x) 1 1 1 1 0 2 2 1 1 1 4 5 4 3 2 21 21 26 17 19 36 34 37 41 45 36 37 31 37 33 100 100 100 100 100 1 2 3 4 5 2011 Totals Pacific Rim 2010 2011 2012 2013 2014 2 1 1 0 0 3 2 2 2 1 5 7 5 4 3 15 15 16 17 19 41 41 40 40 42 34 34 36 37 35 100 100 100 100 100 Ratings (x) 0 1 0 3 2 1 3 2 1 6 4 3 28 30 31 10 11 14 50 50 50 3 12 45 148 190 398 3.980 1.101 2012 Totals Ratings (x) Frequency (f) 1 2 5 17 34 41 100 f*x 2 8 54 140 200 404 f*(x-mean)^2 16.32 18.48 16.65 19.47 0.06 36.86 107.84 f*x 2 10 51 136 205 404 f*(x-mean)^2 16.32 18.48 20.81 18.39 0.05 37.79 111.84 2013 Totals Ratings (x) 1 2 3 4 5 2014 Totals Frequency (f) ### 2 3 15 31 49 100 Totals Ratings (x) f*x 2 8 45 132 230 417 f*(x-mean)^2 20.10 18.84 20.53 0.95 31.69 92.11 Totals Ratings (x) 2 6 45 124 245 422 f*(x-mean)^2 20.74 14.79 22.33 1.50 29.81 89.16 Mean Sample Std Dev 4.220 0.949 4.000 1.054 f*x 3 12 51 144 185 395 f*(x-mean)^2 15.60 26.11 22.82 15.34 0.09 40.79 120.75 Totals Ratings (x) f*x 2 12 57 148 180 399 f*(x-mean)^2 17.88 23.76 18.62 0.00 36.72 96.99 Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### 2 5 19 37 37 100 Totals Ratings (x) f*x 2 10 60 148 180 400 f*(x-mean)^2 18.00 20.00 20.00 36.00 94.00 Totals Ratings (x) 2 10 57 148 185 402 f*(x-mean)^2 18.24 20.40 19.77 0.01 35.53 93.96 Mean Sample Std Dev 4.020 0.974 3.970 1.039 f*x 2 10 63 136 185 396 f*(x-mean)^2 15.68 17.52 19.21 19.35 0.05 40.02 111.84 3.960 1.063 Totals Ratings (x) f*x 3.900 0.990 Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### ### ### 19 45 33 100 1 6 51 164 185 407 f*(x-mean)^2 16.56 9.42 12.85 19.46 0.20 32.00 90.51 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 ### 3 17 41 37 100 1 8 78 148 155 390 f*(x-mean)^2 15.21 8.41 14.44 21.06 0.37 37.51 97.00 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 ### 4 26 37 31 100 4.000 0.974 f*x f*x Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 5 21 34 37 100 2 8 63 144 180 397 f*(x-mean)^2 15.76 17.64 15.52 19.76 0.03 38.19 106.91 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 4 21 36 36 100 3.990 0.990 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 5 20 37 36 100 Ratings (x) 3.950 1.104 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 6 19 37 36 100 4.170 0.965 f*x f*x Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 3 6 17 36 37 100 2 10 54 144 190 400 f*(x-mean)^2 16.00 18.00 20.00 18.00 38.00 110.00 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 5 18 36 38 100 4.040 1.063 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 4 15 33 46 100 Ratings (x) 4.040 1.044 Mean Sample Std Dev 1 2 3 4 5 China 2012 2013 2014 Frequency (f) 1 2 4 18 35 40 100 f*x Mean Sample Std Dev Europe 2010 2011 2012 2013 2014 Frequency (f) 1 3 6 15 37 38 100 f*(x-mean)^2 15.84 26.64 23.52 14.41 0.01 39.54 119.96 Mean Sample Std Dev 1 2 3 4 5 2010 1 1 0 0 0 EUROPE 100 South America 2010 2011 2012 2013 2014 SOUTH AMERICA f*x 4.070 0.956 f*x 1 4 57 180 165 407 f*(x-mean)^2 9.42 8.57 21.75 0.22 28.54 68.51 Mean Sample Std Dev 4.070 0.832 PACIFIC RIM Ratings (x) Totals Ratings (x) f*x 3.920 1.134 Totals Ratings (x) f*x Totals Ratings (x) f*x 2 10 48 160 180 400 f*(x-mean)^2 16.00 18.00 20.00 16.00 36.00 106.00 Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### ### 3 19 42 35 100 1 2 3 4 5 Totals Frequency (f) ### - f*x 2 8 51 160 185 406 f*(x-mean)^2 18.73 16.97 19.10 0.14 32.69 87.64 Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### - 1 6 57 168 175 407 f*(x-mean)^2 9.42 12.85 21.75 0.21 30.27 74.51 Mean Sample Std Dev 4.070 0.868 - f*x Mean Sample Std Dev Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### 3 3 6 28 10 50 f*x 3 6 18 112 50 189 f*(x-mean)^2 f*(x-mean)^2 f*(x-mean)^2 23.19 9.51 3.65 1.36 14.88 52.58 Mean 3.780 Sample Std Dev N/A (sample size is 1) 4.060 0.941 f*x f*x Mean Sample Std Dev 4.000 1.035 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) ### 2 4 17 40 37 100 Ratings (x) 3.950 1.058 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 5 16 40 36 100 2 14 45 164 170 395 f*(x-mean)^2 15.60 17.41 26.62 13.54 0.10 37.49 110.75 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 7 15 41 34 100 3 10 45 164 170 392 f*(x-mean)^2 30.73 25.58 18.43 12.70 0.26 39.66 127.36 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 2 3 5 15 41 34 100 CHINA Ratings (x) Totals Ratings (x) 1 2 3 4 5 Totals Frequency (f) ### ### 1 ### 31 14 50 2 4 12 120 55 193 f*(x-mean)^2 14.90 16.36 6.92 2.96 0.59 14.30 56.02 Mean Sample Std Dev 1 2 3 4 5 Frequency (f) 1 2 ### 4 30 11 50 f*x 3.860 1.069 f*x 1 2 9 124 70 206 f*(x-mean)^2 9.73 4.49 3.76 0.45 10.84 29.28 Mean Sample Std Dev 4.120 0.773 2014 Customer Survey Region Quality Ease of Us Price Service NA NA NA NA NA NA NA NA NA NA 4 4 4 5 5 5 5 5 4 4 1 4 5 4 4 5 4 5 4 5 3 4 4 4 5 3 4 4 4 4 4 5 3 4 4 5 2 5 5 5 NA NA NA NA 4 5 5 4 5 5 4 5 1 4 3 4 4 4 3 4 NA NA NA NA NA NA NA NA 5 5 5 5 4 4 4 4 4 5 4 4 5 4 4 3 3 2 2 2 4 5 2 3 5 5 5 5 4 4 4 4 NA 5 5 2 5 5 5 5 4 5 5 5 4 4 5 5 5 5 5 3 4 5 5 4 4 1 4 5 4 3 5 4 5 5 4 4 2 5 5 4 5 3 1 3 4 2 4 4 4 3 5 5 3 4 4 5 5 4 5 4 4 4 4 5 NA NA NA NA NA NA NA NA 4 5 5 5 5 3 5 5 3 4 4 5 4 4 4 5 3 4 3 1 5 3 2 4 5 3 4 5 4 4 4 5 NA 5 5 3 5 5 5 5 5 5 5 4 5 5 5 4 5 4 5 4 4 4 4 4 5 4 3 4 5 5 4 4 5 5 4 4 4 1 5 3 4 5 4 5 4 4 5 5 5 4 4 5 4 5 4 5 5 4 5 5 4 5 4 4 NA NA NA NA NA NA NA NA 5 5 5 4 4 5 5 5 5 4 4 4 4 4 4 4 3 4 5 5 4 4 3 5 5 4 2 5 5 4 5 4 NA 5 5 4 5 5 5 5 5 4 3 4 4 3 4 4 5 5 4 5 4 5 1 3 2 4 2 5 5 5 5 5 Service 5 NA NA NA NA NA NA NA Price 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Ease of Use 5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA - Descriptive Statistics Quality Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count 4.6 Mean 0.065134 Standard Error 5 Median 5 Mode 0.651339 Standard Deviation 0.424242 Sample Variance 8.427294 Kurtosis -2.282806 Skewness 4 Range 1 Minimum 5 Maximum 460 Sum 100 Count SA - Descriptive Statistics Quality Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count 4.28 Mean 0.110804 Standard Error 4 Median 4 Mode 0.783503 Standard Deviation 0.613878 Sample Variance 4.903883 Kurtosis -1.607279 Skewness 4 Range 1 Minimum 5 Maximum 214 Sum 50 Count Eur - Descriptive Statistics Quality Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Ease of Use 4.1 Mean 0.15425 Standard Error 4 Median 4 Mode 0.844863 Standard Deviation 0.713793 Sample Variance -0.385773 Kurtosis -0.566081 Skewness 3 Range 2 Minimum 5 Maximum 123 Sum 30 Count Pac - Descriptive Statistics Quality Mean Standard Error Median Mode Ease of Use Ease of Use 4.4 Mean 0.221108 Standard Error 4.5 Median 5 Mode 4.27 Mean 0.082701 Standard Error 4 Median 4 Mode 0.827006 Standard Deviation 0.683939 Sample Variance 4.015853 Kurtosis -1.636641 Skewness 4 Range 1 Minimum 5 Maximum 427 Sum 100 Count Price 3.92 Mean 0.10238 Standard Error 4 Median 4 Mode 0.723935 Standard Deviation 0.524082 Sample Variance 5.215213 Kurtosis -1.558311 Skewness 4 Range 1 Minimum 5 Maximum 196 Sum 50 Count Price 4.333333 Mean 0.120662 Standard Error 4 Median 4 Mode 0.660895 Standard Deviation 0.436782 Sample Variance -0.619707 Kurtosis -0.48351 Skewness 2 Range 3 Minimum 5 Maximum 130 Sum 30 Count Price 3.9 Mean 0.276887 Standard Error 4 Median 4 Mode 3.71 Mean 0.110367 Standard Error 4 Median 4 Mode 1.103667 Standard Deviation 1.218081 Sample Variance 0.013829 Kurtosis -0.779332 Skewness 4 Range 1 Minimum 5 Maximum 371 Sum 100 Count 4.31 0.074799 4 5 0.747994 0.559495 1.006914 -1.021896 3 2 5 431 100 Service 3.5 Mean 0.149147 Standard Error 4 Median 4 Mode 1.05463 Standard Deviation 1.112245 Sample Variance -0.281589 Kurtosis -0.598062 Skewness 4 Range 1 Minimum 5 Maximum 175 Sum 50 Count 4.24 0.116269 4 4 0.822143 0.675918 3.444965 -1.397756 4 1 5 212 50 Service 3.9 Mean 0.199712 Standard Error 4 Median 4 Mode 1.09387 Standard Deviation 1.196552 Sample Variance 1.708055 Kurtosis -1.314259 Skewness 4 Range 1 Minimum 5 Maximum 117 Sum 30 Count 3.866667 0.184037 4 4 1.008014 1.016092 1.093373 -1.015136 4 1 5 116 30 Service 4.1 Mean 0.179505 Standard Error 4 Median 4 Mode 4.3 0.213437 4 4 NA NA NA NA NA NA NA NA 5 4 3 1 4 5 4 5 5 4 2 4 5 5 5 5 4 3 4 3 3 4 5 4 4 5 5 4 5 4 5 5 NA NA NA NA NA 5 4 5 5 5 5 2 4 4 5 4 4 5 5 4 4 5 4 4 3 NA NA NA 5 4 5 5 5 5 5 5 4 4 4 5 5 4 5 4 4 5 5 5 5 5 3 2 5 4 5 4 4 4 3 4 0.875595 Standard Deviation 0.766667 Sample Variance 1.830948 Kurtosis -1.017941 Skewness 3 Range 2 Minimum 5 Maximum 39 Sum 10 Count 0.567646 Standard Deviation 0.322222 Sample Variance 1.498216 Kurtosis 0.09112 Skewness 2 Range 3 Minimum 5 Maximum 41 Sum 10 Count 0.674949 0.455556 -0.282995 -0.433637 2 3 5 43 10 5 NA NA NA NA NA 0.699206 Standard Deviation 0.488889 Sample Variance -0.146104 Kurtosis -0.780106 Skewness 2 Range 3 Minimum 5 Maximum 44 Sum 10 Count 5 3 5 NA Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Region Quality Ease of Us Price Service SA SA SA SA SA SA SA SA 5 5 5 4 5 4 5 4 4 4 4 2 4 5 4 5 3 2 5 4 4 2 4 3 5 4 5 5 5 5 4 5 SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA SA 4 4 5 3 5 5 4 4 1 5 4 4 5 4 4 3 5 4 4 4 4 4 5 4 5 5 4 4 5 5 5 3 4 4 5 4 5 5 5 3 4 4 4 4 4 3 4 4 4 4 5 4 4 4 4 4 4 3 4 4 5 1 5 4 4 4 5 5 4 4 4 4 4 4 3 4 4 3 3 4 4 4 4 3 4 2 3 5 3 2 3 3 3 2 4 5 2 5 4 4 4 4 5 4 4 4 3 4 4 4 2 4 4 4 1 4 5 2 3 4 5 4 4 3 1 4 3 4 4 5 4 5 4 5 4 4 4 5 4 5 3 5 4 1 5 5 4 5 4 5 3 4 4 5 5 4 4 5 4 3 3 5 5 4 4 4 4 3 Region Eur Eur Eur Eur Eur Quality Ease of Us Price 4 4 3 3 4 5 4 4 4 4 Service 5 4 5 1 5 3 2 4 3 5 CHN - Descriptive Statistics Quality Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Ease of Use 3.8 Mean 0.290593 Standard Error 4 Median 4 Mode 0.918937 Standard Deviation 0.844444 Sample Variance 0.396221 Kurtosis -0.601382 Skewness 3 Range 2 Minimum 5 Maximum 38 Sum 10 Count Price 4.1 Mean 0.179505 Standard Error 4 Median 4 Mode 0.567646 Standard Deviation 0.322222 Sample Variance 1.498216 Kurtosis 0.09112 Skewness 2 Range 3 Minimum 5 Maximum 41 Sum 10 Count Service 3 Mean 0.210819 Standard Error 3 Median 3 Mode 0.666667 Standard Deviation 0.444444 Sample Variance 0.080357 Kurtosis 0 Skewness 2 Range 2 Minimum 4 Maximum 30 Sum 10 Count 2.6 0.266667 3 3 0.843274 0.711111 0.370396 -0.389108 3 1 4 26 10 Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Eur Region 5 5 4 3 3 4 5 5 5 3 4 4 5 4 3 4 5 5 4 4 5 2 5 4 5 Quality Pac Pac Pac Pac Pac Pac Pac Pac Pac Pac Region China China China China China China China China China China 5 5 5 4 5 4 4 3 5 4 5 5 4 5 5 4 5 3 5 3 4 4 4 5 4 5 5 5 4 3 5 5 4 4 4 4 4 4 4 3 4 3 4 2 4 3 4 5 4 1 Ease of Us Price 5 5 4 4 5 4 5 4 3 5 Quality 4 5 4 3 4 4 5 2 4 4 Service 4 5 4 4 5 4 4 3 4 4 Ease of Us Price 5 5 4 4 4 4 4 3 3 2 5 5 4 4 4 4 4 4 4 3 5 1 4 4 3 4 5 4 5 4 5 4 5 4 4 2 4 5 4 4 3 4 4 3 5 5 5 4 4 4 4 5 3 4 5 Service 4 4 3 3 3 3 3 3 2 2 4 3 3 3 2 3 2 3 2 1 Response times to customer service calls Q1 2013 Q2 2013 Q3 2013 Q4 2013 Q1 2014 Q2 2014 Q3 2014 Q4 2014 4.36 5.42 5.50 2.79 5.55 3.65 8.02 4.00 3.34 4.92 3.55 3.52 1.25 4.33 4.73 1.63 4.21 6.89 0.92 5.27 0.90 3.85 5.00 3.52 5.20 5.13 3.71 2.52 2.69 3.47 5.12 1.00 3.44 6.04 2.53 2.39 3.26 4.68 3.59 4.44 4.07 5.11 3.49 4.69 6.36 8.26 1.91 8.93 6.85 5.69 3.05 5.91 2.75 3.24 4.35 5.58 2.89 5.09 2.33 1.69 3.88 3.39 5.14 0.98 2.34 3.45 1.95 2.77 1.83 3.72 4.59 1.17 1.46 1.90 2.95 4.69 3.34 3.59 1.67 2.58 3.47 3.12 1.00 5.40 3.90 4.49 2.06 4.49 3.57 3.41 3.31 2.55 2.30 1.04 1.59 3.11 4.05 3.38 1.26 0.90 2.31 2.71 1.65 3.58 2.18 4.35 2.46 5.29 1.00 2.18 1.07 2.86 4.44 1.00 1.82 3.74 2.80 3.06 2.40 4.03 2.39 1.63 2.79 2.09 4.28 2.96 3.78 2.87 2.07 2.90 2.58 5.50 2.47 4.24 1.88 4.25 5.08 4.40 1.64 6.40 3.68 3.92 4.13 3.34 3.28 3.24 3.25 5.20 5.28 4.33 4.64 2.65 3.42 3.97 1.26 6.16 6.40 1.00 3.63 5.34 3.74 5.63 4.55 2.13 5.24 4.08 4.04 5.09 7.66 4.65 0.90 2.01 1.34 8.05 4.91 5.06 3.26 4.26 1.70 2.30 5.35 2.33 3.67 4.73 1.05 2.67 4.16 0.90 3.51 5.95 2.05 8.21 2.52 3.99 2.59 1.34 4.87 6.76 2.84 1.25 3.43 2.98 4.65 2.66 4.99 3.76 3.12 2.12 4.32 3.61 4.02 2.63 4.47 4.18 4.73 2.65 2.36 3.64 5.62 0.90 6.40 3.21 3.55 5.93 5.52 4.96 4.85 5.57 4.82 3.18 6.11 4.78 4.13 7.17 5.70 1.00 3.40 2.04 4.37 2.47 3.20 5.83 3.94 2.47 3.89 6.88 1.71 6.39 6.57 4.18 8.82 3.35 5.50 6.51 0.90 2.87 7.45 3.49 3.03 7.46 4.84 2.88 0.95 3.05 1.59 3.05 1.50 5.58 3.11 1.08 3.63 1.86 1.90 6.07 1.00 1.00 1.19 3.79 5.86 0.90 2.24 0.90 3.87 2.46 3.84 2.43 1.54 0.90 3.69 1.73 3.52 2.23 5.35 5.11 6.46 5.61 3.63 3.87 2.40 4.44 4.96 4.41 3.40 3.15 4.87 3.97 3.85 2.81 1.76 5.58 4.92 2.63 3.27 2.86 3.83 1.79 2.70 3.61 0.90 3.38 4.38 2.87 2.11 2.86 3.12 1.86 2.41 2.98 0.90 1.01 4.56 5.67 4.47 1.94 3.90 3.32 2.20 3.52 2.31 1.00 5.90 1.09 4.60 3.52 4.14 4.13 2.43 2.34 2.53 4.14 2.65 3.21 3.85 2.20 4.57 2.99 4.19 3.03 1.90 2.09 1.03 2.95 7.42 3.79 2.48 2.71 0.90 4.87 3.11 0.90 3.52 3.18 0.90 1.35 1.62 1.87 1.03 2.31 1.99 3.97 1.00 3.51 2.41 2.47 4.02 2.03 3.62 4.12 1.40 2.49 2.67 4.33 1.95 2.70 1.76 2.64 4.49 1.62 1.10 4.50 Q1 2013 Q2 2013 Q3 2013 Q4 2013 Q1 2014 Q2 2014 Q3 2014 Q4 2014 Mean 3.915954 Mean 3.725061 Mean 3.747364 Mean 4.452931 Mean 3.088339 Mean 3.113753 Mean 3.202707 Mean 2.52783 Standard Er 0.209586 Standard Er 0.270961 Standard Er 0.197834 Standard Er 0.299608 Standard Er 0.224187 Standard Er 0.173692 Standard Er 0.180934 Standard Er 0.159925 Median 3.828707 Median 4.012614 Median 3.601592 Median 4.15441 Median 2.972192 Median 3.050194 Median 3.16401 Median 2.477405 Mode #N/A Mode 0.9 Mode #N/A Mode 1 Mode 0.9 Mode 0.9 Mode 1 Mode 0.9 Standard D 1.481995 Standard D 1.91598 Standard D 1.398896 Standard D 2.118546 Standard D 1.585239 Standard D 1.228186 Standard D 1.279396 Standard D 1.130838 Sample Var 2.196311 Sample Var 3.670981 Sample Var 1.956909 Sample Var 4.488236 Sample Var 2.512983 Sample Var 1.508441 Sample Var 1.636855 Sample Var 1.278794 Kurtosis 0.093419 Kurtosis -0.337127 Kurtosis -0.36298 Kurtosis -0.690509 Kurtosis -0.808183 Kurtosis -0.671958 Kurtosis 1.300137 Kurtosis -0.983107 Skewness 0.223205 Skewness 0.323839 Skewness 0.00521 Skewness 0.224186 Skewness 0.414716 Skewness 0.089431 Skewness 0.652159 Skewness 0.232659 Range 7.019138 Range 7.312489 Range 5.856213 Range 8.029614 Range 5.555462 Range 4.766075 Range 6.419242 Range 3.972438 Minimum 1 Minimum 0.9 Minimum 0.9 Minimum 0.9 Minimum 0.9 Minimum 0.9 Minimum 1 Minimum 0.9 Maximum 8.019138 Maximum 8.212489 Maximum 6.756213 Maximum 8.929614 Maximum 6.455462 Maximum 5.666075 Maximum 7.419242 Maximum 4.872438 Sum 195.7977 Sum 186.253 Sum 187.3682 Sum 222.6465 Sum 154.417 Sum 155.6876 Sum 160.1354 Sum 126.3915 Count 50 Count 50 Count 50 Count 50 Count 50 Count 50 Count 50 Count 50 Defects After Delivery Defects per million items received from suppliers Month January February March April May June July August September October November December 2010 2011 2012 2013 2014 812 810 813 823 832 848 837 831 827 838 826 819 828 832 847 839 832 840 849 857 839 842 828 816 824 836 818 825 804 812 806 798 804 713 705 686 682 695 692 686 673 681 696 688 671 645 617 603 571 575 547 542 532 496 472 460 441 445 438 436 2010 2011 2012 2013 2014 Mean 826.3333 Mean 837.4167 Mean 785.9167 Mean 669.0833 Mean 496.25 Standard Er 3.35824 Standard Er 3.182476 Standard Er 15.13748 Standard Er 8.941272 Standard Er 15.65254 Median 826.5 Median 839 Median 805 Median 681.5 Median 484 Mode #N/A Mode 828 Mode 804 Mode #N/A Mode #N/A Standard D 11.63329 Standard D 11.02442 Standard D 52.43777 Standard D 30.97347 Standard D 54.22198 Sample Var 135.3333 Sample Var 121.5379 Sample Var 2749.72 Sample Var 959.3561 Sample Var 2940.023 Kurtosis -0.580251 Kurtosis 0.253354 Kurtosis -0.21001 Kurtosis 0.807776 Kurtosis -1.748963 Skewness 0.218469 Skewness -0.142076 Skewness -1.212021 Skewness -1.392782 Skewness 0.271461 Range 38 Range 41 Range 150 Range 93 Range 139 Minimum 810 Minimum 816 Minimum 686 Minimum 603 Minimum 436 Maximum 848 Maximum 857 Maximum 836 Maximum 696 Maximum 575 Sum 9916 Sum 10049 Sum 9431 Sum 8029 Sum 5955 Count 12 Count 12 Count 12 Count 12 Count 12 Mower Unit Sales Month NA SA Europe Pacific China NA World Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 6000 7950 8100 9050 9900 10200 8730 8140 6480 5990 5320 4640 5980 200 220 250 280 310 300 280 250 230 220 210 180 210 720 990 1320 1650 1590 1620 1590 1560 1590 1320 990 660 690 100 120 110 120 130 120 140 130 130 120 130 140 140 0 0 0 0 0 0 0 0 0 0 0 0 0 7020 9280 9780 11100 11930 12240 10740 10080 8430 7650 6650 5620 7020 Feb-11 Mar-11 Apr-11 May-11 Jun-11 7620 8370 8830 9310 10230 240 250 290 330 310 1020 1290 1620 1650 1590 150 140 150 130 140 0 0 0 0 0 9030 10050 10890 11420 12270 Jul-11 8720 290 1560 150 0 10720 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 7710 6320 5840 4960 4350 6020 7920 8430 9040 9820 10370 9050 7620 6420 5890 5340 4430 6100 8010 8430 9110 9730 10120 9080 7820 6540 6010 5270 5380 6210 8030 8540 9120 9570 10230 9580 7680 6870 5930 5260 4830 270 250 250 240 210 220 250 270 310 360 330 310 300 280 270 260 230 250 270 280 320 380 360 320 310 300 290 270 260 270 280 300 340 390 380 350 340 320 310 300 290 1530 1590 1260 900 660 570 840 1110 1500 1440 1410 1440 1410 1350 1080 840 510 480 750 1140 1410 1340 1360 1410 1490 1310 980 770 430 400 750 970 1310 1260 1240 1300 1250 1210 970 650 300 140 150 160 150 150 160 150 160 170 160 170 160 170 180 180 190 180 200 190 200 210 190 200 200 210 220 210 220 230 200 190 210 220 200 210 230 220 220 230 240 230 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 16 22 26 14 15 11 3 1 9650 8310 7510 6250 5370 6970 9160 9970 11020 11780 12280 10960 9500 8230 7420 6630 5350 7030 9220 10050 11050 11640 12040 11010 9830 8370 7490 6530 6300 7080 9250 10020 10995 11436 12082 11486 9504 8635 7451 6453 5651 Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count SA Europe Pacific World 7542.333 Mean 282.3333 Mean 1149 Mean 172.5 Mean 1.883333 Mean 9148.05 227.3237 Standard Er 6.108097 Standard Er 48.70278 Standard Er 4.810681 Standard Er 0.709138 Standard Er 267.2965 7870 Median 280 Median 1260 Median 170 Median 0 Median 9390 9050 Mode 250 Mode 1590 Mode 150 Mode 0 Mode 7020 1760.842 Standard D 47.31312 Standard D 377.2501 Standard D 37.26338 Standard D 5.492959 Standard D 2070.47 3100564 Sample Var 2238.531 Sample Var 142317.6 Sample Var 1388.559 Sample Var 30.1726 Sample Var 4286845 -1.235461 Kurtosis -0.292972 Kurtosis -0.846354 Kurtosis -1.194524 Kurtosis 9.219256 Kurtosis -1.18915 -0.118689 Skewness 0.17792 Skewness -0.533711 Skewness 0.044603 Skewness 3.117068 Skewness -0.188903 6020 Range 210 Range 1350 Range 140 Range 26 Range 6930 4350 Minimum 180 Minimum 300 Minimum 100 Minimum 0 Minimum 5350 10370 Maximum 390 Maximum 1650 Maximum 240 Maximum 26 Maximum 12280 452540 Sum 16940 Sum 68940 Sum 10350 Sum 113 Sum 548883 60 Count 60 Count 60 Count 60 Count 60 Count 60 Correllation between Monthly Mower Sales & Industry Mower Sales NA Correllation China SA Europe Pacific 0.995798 0.757116 0.979208 0.990159 China n/a World 0.99048 Industry Mower Total Sales Month NA SA Eur Pac China World Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 60000 77184 77885 86190 96117 97143 84757 79804 64800 59307 52157 45049 58627 571 611 658 778 886 882 848 735 657 595 553 462 553 13091 17679 22759 27966 27895 30566 29444 28364 28393 24444 18000 12453 12778 1045 1111 1068 1237 1313 1176 1359 1238 1215 1154 1262 1386 1443 74662 96585 102369 116171 126210 129768 116409 110141 95065 85500 71972 59349 73401 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Jul-11 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 76200 82871 84904 93100 93000 83048 74854 60769 55619 48155 42647 57885 77647 81845 86095 91776 100680 86190 71887 60000 55566 50857 42596 58095 75566 80286 85140 90093 95472 87308 74476 61698 57238 50673 51238 59712 77961 83725 90297 91143 99320 93922 73143 66699 56476 51068 46893 615 658 784 846 838 763 694 625 610 571 512 537 595 659 756 878 825 756 714 651 643 619 548 581 614 622 727 826 783 681 646 625 617 587 591 563 571 625 723 848 792 745 739 667 660 625 608 18214 23889 29455 29464 27414 27368 27321 29444 23774 17308 12941 10962 15273 20556 26786 24828 24737 24828 25179 24545 19286 15273 9107 8571 13158 19655 25179 23103 24286 24737 26607 22982 16897 13750 7818 7547 13889 18302 25192 24706 25306 27083 26042 26304 22558 14773 6977 1515 1373 1442 1215 1333 1415 1296 1402 1468 1351 1389 1509 1402 1524 1574 1468 1560 1441 1545 1667 1698 1810 1731 1887 1845 1923 1981 1810 1942 1961 2000 2075 2019 2095 2150 1852 1743 1892 2037 1887 1944 2170 2037 2018 2072 2182 2035 96545 108791 116584 124625 122585 112594 104164 92241 81470 67386 57489 70892 94917 104583 115211 118949 127801 113216 99325 86863 77193 68558 53982 69135 91182 102486 113027 115832 122482 114686 103729 87381 76771 67105 61797 69673 94165 104544 118250 118583 127363 123919 101961 95688 81766 68648 56510 NA SA Eur Pac Mean 72580.89 Mean 675.8406 Mean 21120.05 Mean 1628.228 Standard Er 2159.846 Standard Er 13.44405 Standard Er 860.5165 Standard Er 42.71701 Median 75883.02 Median 654.1528 Median 23831.24 Median 1552.544 Mode 60000 Mode 625 Mode 29444.44 Mode 1214.953 Standard D 16730.09 Standard D 104.1372 Standard D 6665.532 Standard D 330.8846 Sample Var 2.8E+008 Sample Var 10844.55 Sample Var44429315 Sample Var 109484.6 Kurtosis -1.254556 Kurtosis -0.706448 Kurtosis -0.84016 Kurtosis -1.326642 Skewness -0.146283 Skewness 0.418732 Skewness -0.600631 Skewness 0.056199 Range 58083.46 Range 424.1758 Range 23589.29 Range 1136.818 Minimum 42596.15 Minimum 461.5385 Minimum 6976.744 Minimum 1045 Maximum 100679.6 Maximum 885.7143 Maximum 30566.04 Maximum 2181.818 Sum 4354853 Sum 40550.44 Sum 1267203 Sum 97693.66 Count 60 Count 60 Count 60 Count 60 China World Mean 96004.17 Standard Er 2816.727 Median 97955.18 Mode #N/A Standard D 21818.27 Sample Var 4.8E+008 Kurtosis -1.135311 Skewness -0.281086 Range 75786.03 Minimum 53981.68 Maximum 129767.7 Sum 5760250 Count 60 Tractor Unit Sales Month NA SA Eur Pac China World Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 570 611 630 684 650 600 512 500 478 455 407 360 571 250 270 260 270 280 270 264 280 290 280 290 280 320 560 600 680 650 580 590 760 645 650 670 888 850 620 212 230 240 263 269 280 290 270 263 258 240 230 250 0 0 0 0 0 0 0 0 0 0 0 0 0 1592 1711 1810 1867 1779 1740 1826 1695 1681 1663 1825 1720 1761 Feb-11 Mar-11 Apr-11 May-11 Jun-11 650 740 840 830 760 350 390 440 470 490 760 742 780 690 721 275 270 280 290 300 0 0 0 0 0 2035 2142 2340 2280 2271 Jul-11 681 481 680 312 0 2154 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 670 640 620 570 533 620 792 890 960 1040 1032 1006 910 803 730 699 647 730 930 1160 1510 1650 1490 1460 1390 1360 1340 1240 1103 1250 1550 1820 2010 2230 2490 2440 2334 2190 2080 2050 2004 460 460 440 436 420 510 590 610 600 620 640 590 600 670 630 710 570 650 680 724 730 760 800 840 830 820 810 827 750 780 805 830 890 930 980 1002 970 960 930 920 902 711 695 650 680 657 610 680 730 820 810 807 760 720 660 630 603 570 500 590 620 730 740 720 670 610 599 560 550 520 480 523 560 570 590 600 580 570 550 530 517 490 305 290 260 250 240 250 250 260 270 290 310 340 320 313 290 280 260 287 290 300 310 330 340 350 341 330 320 300 290 200 210 220 230 253 270 280 250 230 220 190 190 0 0 0 0 0 10 12 20 22 20 24 20 31 30 37 32 33 35 50 63 68 70 82 80 90 100 102 110 114 111 121 123 120 130 136 134 132 137 130 139 131 2146 2085 1970 1936 1850 2000 2324 2510 2672 2780 2813 2716 2581 2476 2317 2324 2080 2202 2540 2867 3348 3550 3432 3400 3261 3209 3132 3027 2777 2821 3209 3553 3820 4133 4476 4436 4256 4067 3890 3816 3717 NA SA Eur Pac China World Mean 1075.033 Mean 598.35 Mean 647.9667 Mean 272.1833 Mean 46.65 Mean 2640.183 Standard Er 75.70645 Standard Er 30.37212 Standard Er 12.1931 Standard Er 5.014188 Standard Er 6.736226 Standard Er 105.0135 Median 835 Median 605 Median 647.5 Median 270 Median 23 Median 2408 Mode 570 Mode 280 Mode 680 Mode 290 Mode 0 Mode 2324 Standard D 586.4197 Standard D 235.2614 Standard D 94.44736 Standard D 38.83974 Standard D 52.17858 Standard D 813.4312 Sample Var 343888 Sample Var 55347.93 Sample Var 8920.304 Sample Var 1508.525 Sample Var 2722.604 Sample Var 661670.3 Kurtosis -0.131806 Kurtosis -1.272932 Kurtosis -0.377763 Kurtosis -0.471209 Kurtosis -1.253821 Kurtosis -0.652117 Skewness 1.005045 Skewness 0.00104 Skewness 0.403752 Skewness -0.086968 Skewness 0.647419 Skewness 0.661644 Range 2130 Range 752 Range 408 Range 160 Range 139 Range 2884 Minimum 360 Minimum 250 Minimum 480 Minimum 190 Minimum 0 Minimum 1592 Maximum 2490 Maximum 1002 Maximum 888 Maximum 350 Maximum 139 Maximum 4476 Sum 64502 Sum 35901 Sum 38878 Sum 16331 Sum 2799 Sum 158411 Count 60 Count 60 Count 60 Count 60 Count 60 Count 60 Correllation between Monthly Tractor Sales & Industry Tractor Sales NA SA Europe Pacific China World Correllatio 0.893424 0.999017 0.918648 0.980329 0.996261 0.960277 Industry Tractor Total Sales Month NA SA Eur Pac China World Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 8143 8592 8630 8947 8442 7500 6145 5882 5595 5233 4494 3913 5938 984 1051 1016 1027 1057 1019 977 1057 1086 1045 1078 1029 1172 5091 5310 6071 5856 5273 5315 7170 5926 6075 6321 8381 7944 5688 987 1090 1127 1209 1221 1327 1324 1268 1209 1168 1127 1085 1185 278 283 285 288 286 287 289 290 293 295 298 301 306 15483 16325 17129 17327 16278 15448 15905 14422 14258 14061 15378 14272 14289 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Jul-11 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 6633 7327 8077 7830 7103 6239 6036 5664 5345 4831 4454 5299 6529 7120 7619 8387 8110 7752 6894 6015 5368 4964 4444 5000 6284 7785 9934 10645 9491 9182 8528 8293 8221 7470 6509 7267 8807 10168 11044 12120 13459 13048 12275 11347 10667 10459 10082 1273 1423 1612 1728 1815 1776 1685 1679 1618 1564 1522 1835 2115 2202 2151 2214 2278 2100 2128 2367 2211 2483 1986 2257 2353 2457 2517 2612 2749 2887 2833 2789 2765 2746 2534 2635 2703 2795 2997 3131 3311 3390 3277 3232 3131 3087 3030 7037 6981 7500 6571 6990 6667 6762 6635 6311 6476 6250 5922 6667 7228 8200 7941 7921 7677 7200 6735 6495 6061 5816 5051 6082 6327 7604 7789 7347 6979 6489 6316 5833 5789 5591 5106 5474 6022 6064 6344 6593 6304 6064 5789 5699 5604 5444 1286 1286 1346 1388 1449 1490 1449 1394 1256 1214 1171 1208 1214 1256 1311 1415 1520 1675 1584 1527 1422 1366 1262 1373 1436 1478 1512 1642 1667 1733 1700 1642 1576 1493 1450 1010 1045 1106 1150 1244 1357 1421 1263 1173 1128 974 979 302 303 307 309 312 315 318 321 315 318 320 333 313 606 571 556 526 513 769 750 732 714 698 714 1063 1264 1333 1556 1739 1702 1915 2083 2128 2292 2245 2292 2449 2400 2353 2600 2653 2600 2549 2453 2517 2541 2453 16530 17320 18842 17826 17669 16487 16250 15692 14844 14402 13716 14597 16836 18412 19852 20513 20355 19716 18575 17394 16226 15587 14207 14394 17218 19310 22901 24244 22993 22483 21465 21123 20523 19789 18329 18311 20477 22489 23607 25439 27374 26764 25428 23995 23142 22666 21989 NA SA Eur Pac China World Mean 7726.268 Mean 2092.908 Mean 6436.15 Mean 1322.727 Mean 1069.885 Mean 18647.94 Standard Er 293.8582 Standard Er 96.84844 Standard Er 107.7077 Standard Er 24.98474 Standard Er 117.1014 Standard Er 467.7558 Median 7559.524 Median 2176.352 Median 6318.272 Median 1298.197 Median 588.7446 Median 17747.65 Mode #N/A Mode 1056.604 Mode 6666.667 Mode 1126.761 Mode 315 Mode #N/A Standard D 2276.216 Standard D 750.1848 Standard D 834.3005 Standard D 193.531 Standard D 907.0633 Standard D 3623.221 Sample Var 5181158 Sample Var 562777.2 Sample Var 696057.3 Sample Var 37454.24 Sample Var 822763.7 Sample Var 13127728 Kurtosis -0.180847 Kurtosis -1.237076 Kurtosis -0.459519 Kurtosis -0.632684 Kurtosis -1.302885 Kurtosis -0.594644 Skewness 0.576295 Skewness -0.060789 Skewness 0.467126 Skewness 0.227442 Skewness 0.682667 Skewness 0.60119 Range 9546.416 Range 2412.387 Range 3330.447 Range 758.3143 Range 2375.061 Range 13657.27 Minimum 3913.043 Minimum 977.4436 Minimum 5050.505 Minimum 974.359 Minimum 278 Minimum 13716.25 Maximum 13459.46 Maximum 3389.831 Maximum 8380.952 Maximum 1732.673 Maximum 2653.061 Maximum 27373.52 Sum 463576.1 Sum 125574.5 Sum 386169 Sum 79363.62 Sum 64193.13 Sum 1118876 Count 60 Count 60 Count 60 Count 60 Count 60 Count 60 Chapter 3 Chapter 3 Project I: Do only: Part 1: a,c,f,g,h Part 2 Part 3 Chapter 4 Dealer Satisfaction North America Scale:0 2010 2011 2012 2013 2014 Scale:1 Scale:2 1 0 0 0 1 1 1 2 2 3 Scale:3 Scale: 4 Scale: 5 2 14 22 2 14 20 1 8 34 6 12 34 5 15 44 11 14 15 45 56 50 50 60 100 125 100% Dealer Satisfaction NA Sample Size 90% 60 80% 70% 50 2010 2011 2012 2013 2014 40 Over the years 2010 through 2014, there is an increase in the number of North America dealers that responded with a rating of 4 and 5 for their overall satisfaction with PLE.The number of dealers with low satisfactory results also increased relatively over the years 2010 through 2012. 2 30 5 12 60% 50% 1 6 2 0 Scale:0 Step 0: Step 1: Step 2: Step 3: Scale:1 Scale:2 Scale:3 Scale: 4 30% 1 0 1 1 Scale:0 0 Scale:1 0% Scale: 5 Rearange data to look like the blue region Select blue region Insert-->Charts Group(Column:Clustered Column ) Insert-->Charts Group(100% Stacked Column ) 1 14 2 Scale:2 34 20 2 14 Scale:3 56 34 8 40% 10% 10 44 3 20% 20 15 22 Scale: 4 45 2014 2013 2012 2011 2010 15 14 11 Scale: 5 Right click on a bar to get the Data Labels 100% stacked column South America Scale:0 2010 2011 2012 2013 2014 0 0 0 0 1 Scale:1 Scale:2 0 0 0 1 1 Scale:3 0 0 1 1 2 2 2 4 3 4 Scale: 4 Scale: 5 6 6 11 12 22 2 2 14 33 60 10 10 30 50 90 70 100% 90% 60 80% 50 70% 2010 2011 2012 2013 2014 40 There is a significant increase in the number of South American dealers that responded with a rating of 5 over the years. 30 20 Europe Scale:0 2010 2011 2012 2013 2014 0 0 0 0 0 Scale:1 Scale:2 0 0 0 0 0 Scale