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Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample

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Dealer SatisfactionDealer Satisfaction Survey Scale:012345Sample North AmericaSize2010102142211502011002142014502012111834156020131261234451002014235154456125South America201000026210201100026210201200141114302013011312335020141124226090Europe201000137415201100128415201200121572520130012216302014001417830Pacific Rim201000122052011001130520120011316201300025310201400127212China2012000100120130014207201400158216 Dealer Satisfaction by Region and Year 0 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 1 0 1 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 0 0 1 2 3 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 2 2 1 6 5 0 0 1 1 2 1 1 1 1 1 1 1 1 0 1 0 1 1 3 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 14 14 8 12 15 2 2 4 3 4 3 2 2 2 4 2 1 1 2 2 1 4 5 4 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 22 20 34 34 44 6 6 11 12 22 7 8 15 21 17 2 3 3 5 7 0 2 8 5 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 11 14 15 45 56 2 2 14 33 60 4 4 7 6 8 0 0 1 3 2 0 0 2 This chart is showing Dealer Satisfaction between North America, South America, Europe, Pacific Rim and China. The data that was selected was rated on a a survery scale from 0-5 and between the the years of 2010-2014, except for China who started later in 2012. North America was leading in sample size and "in 5s" dealer satisfacion for "excelltence". Although North America recieved the highest total numbers in dealer satisfactions for excellent rankings, in 2014, South America recieved 60 surverys and North America recieved 56 within the level 5 category. End-User SatisfactionEnd-User SatisfactionSample North America012345Size20101361537381002011124183540100201212517344110020130241533461002014023153149100South America20101251836381002011136173637100201202619373610020130252037361002014025193737100Europe20101242136361002011125213437100201211426373110020131131741371002014012194533100Pacific Rim20102351541341002011127154134100201212516403610020130241740371002014013194235100China201203362810502013122430115020140113311450 End-User Satisfaction by Region and Year 0 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 1 1 1 0 0 1 1 0 0 0 1 1 1 1 0 2 1 1 0 0 0 1 0 1 2010 2011 2012 2013 2014 ...

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Dealer SatisfactionDealer Satisfaction Survey Scale:012345Sample North AmericaSize201010214221150201100214201450201211183415 6020131261234451002014235154456125South America2010000262102011000262102012001411143020130113 12335020141124226090Europe201000137415201100128415201 200121572520130012216302014001417830Pacific Rim2010001220520110011305201200113162013000253102014 00127212China2012000100120130014207201400158216 Dealer Satisfaction by Region and Year 0 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 1 0 1 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 0 0 1 2 3 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 2 2 1 6 5 0 0 1 1 2 1 1 1 1 1 1 1 1 0 1 0 1 1 3 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 14 14 8 12 15 2 2 4 3 4 3 2 2 2 4 2 1 1 2 2 1 4 5 4 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 22 20 34 34 44 6 6 11 12 22 7 8 15 21
17 2 3 3 5 7 0 2 8 5 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 11 14 15 45 56 2 2 14 33 60 4 4 7 6 8 0 0 1 3 2 0 0 2 This chart is showing Dealer Satisfaction between North America, South America, Europe, Pacific Rim and China. The data that was selected was rated on a a survery scale from 0-5 and between the the years of 2010-2014, except for China who started later in 2012. North America was leading in sample size and "in 5s" dealer satisfacion for "excelltence". Although North America recieved the highest total numbers in dealer satisfactions for excellent rankings, in 2014, South America recieved 60 surverys and North America recieved 56 within the level 5 category. End-User SatisfactionEnd-User SatisfactionSample North America012345Size201013615373810020111241835401002012 12517344110020130241533461002014023153149100South America2010125183638100201113617363710020120261937361 0020130252037361002014025193737100Europe2010124213636 10020111252134371002012114263731100201311317413710020 14012194533100Pacific Rim2010235154134100201112715413410020121251640361002 0130241740371002014013194235100China20120336281050201 3122430115020140113311450 End-User Satisfaction by Region and Year 0 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 1 1 1 0 0 1 1 0 0 0 1 1 1 1
0 2 1 1 0 0 0 1 0 1 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 3 2 2 2 2 2 3 2 2 2 2 2 1 1 1 3 2 2 2 1 3 2 1 2 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 6 4 5 4 3 5 6 6 5 5 4 5 4 3 2 5 7 5 4 3 3 2 1 3 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 15 18 17 15 15 18 17 19 20 19 21 21 26 17 19 15 15 16 17 19 6 4 3 4 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 37 35 34 33 31 36 36 37 37 37 36 34 37 41 45 41 41 40 40 42 28 30 31 5 2010 2011 2012 2013 2014 South America 2010 2011 2012 2013 2014 Europe 2010 2011 2012 2013 2014 Pacific Rim 2010 2011 2012 2013 2014 China 2012 2013 2014 38 40 41 46 49 38 37 36 36 37 36 37 31 37 33 34 34 36 37 35 10 11 14 This chart is showing End-User Satisfaction between North America, South America, Europe, Pacific Rim and China. The data that was selected was rated on a a survery scale from 0-5 and between the the years of 2010-2014, except for China who started later in 2012. North America, South America, Europe, and the Pacific Rim all have the same sample size of 100 for
each year between 2010 through 2014. China has a smaller sample size of 50 between the years of 2012 through 2014. You can see that the ratings of 5's, 4's, and 3's are the highest ratings. North America's rating of 4 decreases every year starting with 2010 while the 5 ratings increase through the years. The Pacfic Rim's 4 ratings are highest rated and is basically constant throughout the years while the 5 ratings are lower then 4 ratings the 5's are constant throughout the years. Complaints ComplaintsMonthWorldNASAEurPacChinaJan- 1016910212523Feb-1018711513554Mar-1021012815616Apr- 1022613616677May-1023213717735Jun-1026115119829Jul- 1024514018807Aug-1022312816763Sep-1019510315734Oct- 101749614622Nov-101548411590Dec-10163999541Jan- 1119512310593Feb-1122114113625Mar-1124015216666Apr- 11264163207011May-1128317822758Jun-11296170288612Jul- 11269153258110Aug-1125614623798Sep-1123113120737Oct- 1121412516685Nov-1120111813664Dec-111719611613Jan- 12200112156643Feb-12216117187164Mar- 12234126207693Apr-122531382379112May- 122821522685145Jun-123051633091156Jul- 122961562889185Aug-122791482686154Sep- 122661432482134Oct-122431312176123Nov- 122321281873103Dec-12203107157074Jan- 13216110197485Feb-132391232379104Mar- 132661382683136Apr-132841503088115May- 133151693391157Jun-133401813795198Jul- 133191693492177Aug-133041603290157Sep- 132771412987146Oct-132501232683126Nov- 132281122477105Dec-13213105237474Jan- 14240121268085Feb-142511262882105Mar- 142811483185125Apr-142981553589136May- 143221683995128Jun-1435018343981511Jul- 1433017041951410Aug-143111583893139Sep- 142891493389117Oct-14265136308586Nov- 14239121268075Dec-14219108237675
Complaints by Month and Region World 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 169 187 210 226 232 261 245 223 195 174 154 163 195 221 240 264 283 296 269 256 231 214 201 171 200 216 234 253 282 305 296 279 266 243 232 203 216 239 266 284 315 340 319 304 277 250 228 213 240 251 281 298 322 350 330 311 289 265 239 219 NA 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 102 115 128 136 137 151 140 128 103 96 84 99 123 141 152 163 178 170 153 146 131 125 118 96 112 117 126 138 152 163 156 148 143 131 128 107 110 123 138 150 169 181 169 160 141 123 112 105 121 126 148 155 168 183 170 158 149 136 121 108 SA 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817
40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 12 13 15 16 17 19 18 16 15 14 11 9 10 13 16 20 22 28 25 23 20 16 13 11 15 18 20 23 26 30 28 26 24 21 18 15 19 23 26 30 33 37 34 32 29 26 24 23 26 28 31 35 39 43 41 38 33 30 26 23 Eur 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 52 55 61 67 73 82 80 76 73 62 59 54 59 62 66 70 75 86 81 79 73 68 66 61 66 71 76 79 85 91 89 86 82 76 73 70 74 79 83 88 91 95 92 90 87 83 77 74 80 82 85 89 95 98 95 93 89 85 80 76 Pac 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852
41883 41913 41944 41974 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 China 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 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 This chart is showing PLE's Complaints from registered customers each month within PLE's 5 regions. From this data we can conclude that there is more use of the equipment in the summer months because of the higher number of complaints recieved. China has the fewest number of compaints, this is due to the less customer usage. Based off the data, the Pacific Rim and South America do not have as many complaints as North America does due to less people using or purchasing PLE's equipment. . Mower Unit SalesMower Unit SalesMonthNASAEuropePacificChinaWorldJan- 10600020072010007020Feb-10795022099012009280Mar-
108100250132011009780Apr-1090502801650120011100May- 1099003101590130011930Jun-10102003001620120012240Jul- 1087302801590140010740Aug-1081402501560130010080Sep- 106480230159013008430Oct-105990220132012007650Nov- 10532021099013006650Dec-10464018066014005620Jan- 11598021069014007020Feb-117620240102015009030Mar- 1183702501290140010050Apr-1188302901620150010890May- 1193103301650130011420Jun-11102303101590140012270Jul- 1187202901560150010720Aug-117710270153014009650Sep- 116320250159015008310Oct-115840250126016007510Nov- 11496024090015006250Dec-11435021066015005370Jan- 12602022057016006970Feb-12792025084015009160Mar- 128430270111016009970Apr-1290403101500170011020May- 1298203601440160011780Jun-12103703301410170012280Jul- 1290503101440160010960Aug-127620300141017009500Sep- 126420280135018008230Oct-125890270108018007420Nov- 12534026084019006630Dec-12443023051018005350Jan- 13610025048020007030Feb-13801027075019009220Mar- 1384302801140200010050Apr-1391103201410210011050May- 1397303801340190011640Jun-13101203601360200012040Jul- 1390803201410200011010Aug-137820310149021009830Sep- 136540300131022008370Oct-13601029098021007490Nov- 13527027077022006530Dec-13538026043023006300Jan- 14621027040020007080Feb-14803028075019009250Mar- 148540300970210010020Apr-1491203401310220510995May- 14957039012602001611436Jun- 141023038012402102212082Jul- 14958035013002302611486Aug-1476803401250220149504Sep- 1468703201210220158635Oct-145930310970230117451Nov- 14526030065024036453Dec-14483029030023015651 Mower Unit Sales by Month and Region NA 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061
41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 6000 7950 8100 9050 9900 10200 8730 8140 6480 5990 5320 4640 5980 7620 8370 8830 9310 10230 8720 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 SA 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 200 220 250 280 310 300 280 250 230 220 210 180 210 240 250 290 330 310 290 270 250 250 240 210 220 250 270 310 360 330 310 300 280 270 260 230 250 270 280 320 380 360 320 310 300 290 270 260 270 280 300 340 390 380 350 340 320 310 300 290 Europe 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852
41883 41913 41944 41974 720 990 1320 1650 1590 1620 1590 1560 1590 1320 990 660 690 1020 1290 1620 1650 1590 1560 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 Pacific 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 100 120 110 120 130 120 140 130 130 120 130 140 140 150 140 150 130 140 150 140 150 160 150 150 160 150 160 170 160 170 160 170 180 180 190 180 200 190 200 210 190 200 200 210 220 210 220 230 200 190 210 220 200 210 230 220 220 230 240 230 China 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 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 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 World 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 416 99 41730 41760 41791 41821 41852 41883 41913 41944 41974 7020 9280 9780 11100 11930 12240 10740 10080 8430 7650 6650 5620 7020 9030 10050 10890 11420 12270 10720 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 The chart identifies the unit sales on PLE's mower equipment. We can see that the highest peak for mower sales is in the summer months and then a decline in sales starting in early fall months. Looking at the chart, North America is the region with the highest unit sales for PLE's mowers. Tractor Unit SalesTractor Unit SalesMonthNASAEurPacChinaWorldJan- 1057025056021201592Feb-1061127060023001711Mar- 1063026068024001810Apr-1068427065026301867May- 1065028058026901779Jun-1060027059028001740Jul- 1051226476029001826Aug-1050028064527001695Sep- 1047829065026301681Oct-1045528067025801663Nov-
1040729088824001825Dec-1036028085023001720Jan- 1157132062025001761Feb-1165035076027502035Mar- 1174039074227002142Apr-1184044078028002340May- 1183047069029002280Jun-1176049072130002271Jul- 1168148168031202154Aug-1167046071130502146Sep- 1164046069529002085Oct-1162044065026001970Nov- 1157043668025001936Dec-1153342065724001850Jan- 12620510610250102000Feb-12792590680250122324Mar- 12890610730260202510Apr-12960600820270222672May- 121040620810290202780Jun-121032640807310242813Jul- 121006590760340202716Aug-12910600720320312581Sep- 12803670660313302476Oct-12730630630290372317Nov- 12699710603280322324Dec-12647570570260332080Jan- 13730650500287352202Feb-13930680590290502540Mar- 131160724620300632867Apr-131510730730310683348May- 131650760740330703550Jun-131490800720340823432Jul- 131460840670350803400Aug-131390830610341903261Sep- 1313608205993301003209Oct-1313408105603201023132Nov- 1312408275503001103027Dec-1311037505202901142777Jan- 1412507804802001112821Feb-1415508055232101213209Mar- 1418208305602201233553Apr-1420108905702301203820May- 1422309305902531304133Jun-1424909806002701364476Jul- 14244010025802801344436Aug-1423349705702501324256Sep- 1421909605502301374067Oct-1420809305302201303890Nov- 1420509205171901393816Dec-1420049024901901313717 Tractor Unit Sales by Month and Region NA 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974
570 611 630 684 650 600 512 500 478 455 407 360 571 650 740 840 830 760 681 670 640 620 570 533 620 792 890 960 1040 1032 1006 910 803 730 699 647 730 930 1160 1510 1650 1490 1460 1390 1360 1340 124 0 1103 1250 1550 1820 2010 2230 2490 2440 2334 2190 2080 2050 2004 SA 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40 848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 250 270 260 270 280 270 264 280 290 280 290 280 320 350 390 440 470 490 481 460 460 440 436 420 510 590 610 600 620 640 590 600 670 630 710 570 650 680 724 730 760 800 840 830 820 810 827 750 780 805 830 890 930 980 1002 970 960 930 920 902 Eur 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 560 600 680 650 580 590 760 645 650 670 888 850 620 760 742 780 690 721 680 711 695 650 680 657 610 680 730 820 810 807 760 720 660 630 603 570 500 590 620 730 740 720 670 610 599 560 550 520 480 523 560
570 590 600 580 570 550 530 517 490 Pac 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 212 230 240 263 269 280 290 270 263 258 240 230 250 275 270 280 290 300 312 305 290 260 250 240 250 250 260 270 290 310 340 320 313 290 280 260 287 290 300 310 330 340 350 341 330 320 300 290 200 210 220 230 253 270 280 250 230 220 190 190 China 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 World 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909
40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 1592 1711 1810 1867 1779 1740 1826 1695 1681 1663 1825 1720 1761 2035 2142 2340 2280 2271 2154 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 The chart identifies the unit sales for PLE's tractor equipment. We can see that throughout the years with the World orange line shown in the graph increases total sales between the years of 2010 to 2014. The line is basically increase in a positive direction on this graph. And the increase in tractor sales increase in each region throughout the years as well. Overall there is a positive correlations between time and tractor unit sales over all of the country regions. Q2Sum of PercentYear20102011201220132014Anova: Single FactorMonthJan98.43%98.44%98.67%98.92%99.21%SUMMAR YFeb98.09%98.63%98.79%98.82%99.14%GroupsCountSumAve rageVarianceMar97.58%98.38%98.67%98.91%99.28%20101211 .819193754498.49%0.000012772Apr98.60%98.73%98.80%98.9 7%99.22%20111211.833727270198.61%0.0000022009May98.7 3%98.73%98.84%99.11%99.22%20121211.853179718798.78%0 .000000506Jun98.64%98.78%98.81%98.91%99.08%20131211.8 72309097698.94%0.0000034754Jul98.58%98.71%98.89%98.99 %99.23%20141211.888252856399.07%0.0000137813Aug98.67 %98.67%98.77%99.12%99.23%Sep98.94%98.58%98.77%98.93
%98.69%Oct98.76%98.69%98.67%98.99%99.23%ANOVANov9 8.50%98.69%98.83%98.43%99.29% Source of VariationSSdfMSFP-valueF critDec98.39%98.33%98.81%99.12%98.01%Between Groups0.000260782140.00006519559.95792072750.000003912 22.5396886349Within Groups0.0003600906550.0000065471Total0.000620872759 On-Time DeliveryMonthNumber of deliveriesNumber On TimePercentJan-101086106998.4%Feb-101101108098.1%Mar- 101116108997.6%Apr-101216119998.6%May- 101183116898.7%Jun-101176116098.6%Jul- 101198118198.6%Aug-101205118998.7%Sep- 101223121098.9%Oct-101209119498.8%Nov- 101198118098.5%Dec-101243122398.4%Jan- 111220120198.4%Feb-111241122498.6%Mar- 111237121798.4%Apr-111258124298.7%May- 111262124698.7%Jun-111227121298.8%Jul- 111243122798.7%Aug-111281126498.7%Sep- 111272125498.6%Oct-111295127898.7%Nov- 111298128198.7%Dec-111318129698.3%Jan- 121281126498.7%Feb-121320130498.8%Mar- 121352133498.7%Apr-121336132098.8%May- 121291127698.8%Jun-121342132698.8%Jul- 121352133798.9%Aug-121377136098.8%Sep- 121385136898.8%Oct-121356133898.7%Nov- 121362134698.8%Dec-121349133398.8%Jan- 131386137198.9%Feb-131358134298.8%Mar- 131371135698.9%Q2Apr-131362134899.0%May- 131350133899.1%Anova: Single FactorJun- 131381136698.9%Jul-131392137899.0%SUMMARYAug- 131371135999.1%GroupsCountSumAverageVarianceSep- 131402138798.9%20101211.819193754498.49%0.000012772Oc t- 131384137099.0%20111211.833727270198.61%0.0000022009N ov- 131399137798.4%20121211.853179718798.78%0.000000506De
c- 131369135799.1%20131211.872309097698.94%0.0000034754J an- 141401139099.2%20141211.888252856399.07%0.0000137813F eb-141388137699.1%Mar-141395138599.3%Apr- 141412140199.2%ANOVAMay-141403139299.2%Source of VariationSSdfMSFP-valueF critJun-141415140299.1%Between Groups0.000260782140.00006519559.95792072750.000003912 22.5396886349Jul-141426141599.2%Within Groups0.0003600906550.0000065471Aug- 141431142099.2%Sep- 141445142698.7%Total0.000620872759Oct- 141425141499.2%Nov-141413140399.3%Dec- 141456142798.0% On Time Delivery by Month Number of deliveries 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 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 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061
41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 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 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 0.98434622467771637 0.98092643051771122 0.97580645161290325 0.98601973684210531 0.9873203719357565 0.98639455782312924 0.9858096828046744 0.98672199170124486 0.98937040065412918 0.98759305210918114 0.9849749582637729 0.98390989541432017 0.98442622950819669 0.98630136986301364 0.98383185125303152 0.9872813990461049 0.98732171156893822 0.98777506112469438 0.98712791633145613 0.98672911787665885 0.98584905660377353 0.98687258687258683 0.98690292758089371 0.98330804248861914 0.98672911787665885 0.98787878787878791 0.98668639053254437 0.9880239520958084 0.98838109992254064 0.98807749627421759
0.98890532544378695 0.98765432098765427 0.98772563176895312 0.98672566371681414 0.98825256975036713 0.98813936249073386 0.98917748917748916 0.98821796759941094 0.98905908096280093 0.98972099853157125 0.99111111111111116 0.98913830557566984 0.98994252873563215 0.99124726477024072 0.98930099857346643 0.98988439306358378 0.98427448177269483 0.99123447772096418 0.99214846538187007 0.99135446685878958 0.99283154121863804 0.99220963172804533 0.99215965787598004 0.99081272084805649 0.99228611500701258 0.99231306778476591 0.98685121107266438 0.99228070175438599 0.99292285916489742 0.98008241758241754 We decided to use a clustered column chart to represent the On- Time deliveries for PLE's unit deliveries. The darker backgorund makes it easier to see the difference in the deliveries and the ones that were delivered on time to the customer. For example, for the month of January of 2010, PLE's had a total of 1086 deliveries but out of that number, 98.4% when delivered on-time. This chart makes is easy to compare those deliveries. Response TimeResponse times to customer service callsQ1 2013Q2 2013Q3 2013Q4 2013Q1 2014Q2 2014Q3 2014Q4 20144.364.333.714.442.753.451.672.555.424.732.524.073.241.9 52.582.305.501.632.695.114.352.773.471.042.794.213.473.495. 581.833.121.595.556.895.124.692.893.721.003.113.650.921.006 .365.094.595.404.058.025.273.448.262.331.173.903.384.000.90 6.041.911.691.464.491.263.343.852.538.933.881.902.060.904.9
25.002.396.853.392.954.492.313.553.523.265.695.144.693.572. 713.525.204.683.050.983.343.411.651.255.133.595.912.343.593 .313.582.185.291.071.002.804.032.792.964.351.002.861.823.06 2.392.093.782.462.184.443.742.401.634.282.872.074.554.876.1 11.592.404.470.902.902.136.764.783.054.441.944.872.585.242. 844.131.504.963.903.115.504.081.257.175.584.413.320.902.474 .043.435.703.113.402.203.524.245.092.981.001.083.153.523.18 1.887.664.653.403.634.872.310.904.254.652.662.041.863.971.0 01.355.080.904.994.371.903.855.901.624.402.013.762.476.072. 811.091.871.641.343.123.201.001.764.601.036.408.052.125.831 .005.583.522.313.684.914.323.941.194.924.141.993.925.063.61 2.473.792.634.133.974.133.264.023.895.863.272.431.003.344.2 62.636.880.902.862.343.513.281.704.471.712.243.832.532.413. 242.304.186.390.901.794.142.473.255.354.736.573.872.702.654 .025.202.332.654.182.463.613.212.035.283.672.368.823.840.90 3.853.624.334.733.643.352.433.382.204.124.641.055.625.501.5 44.384.571.402.652.670.906.510.902.872.992.493.424.166.400. 903.692.114.192.673.970.903.212.871.732.863.034.331.263.513 .557.453.523.121.901.956.165.955.933.492.231.862.092.706.40 2.055.523.035.352.411.031.761.008.214.967.465.112.982.952.6 43.632.524.854.846.460.907.424.495.343.995.572.885.611.013. 791.623.742.594.820.953.634.562.481.105.631.343.183.053.875 .672.714.50 Response Time by Quarter and Year Q1 2013 4.356805690747569 5.415645561640849 5.50147957886802 2.7866492627596018 5.5495684291032372 3.6535666521900567 8.0191382648423311 4.0045367922517467 3.3431904438999482 4.9159115332600773 3.5546503494857462 3.5231651208392578 1.2533953549223953 2.1813659868144897 4.3525112841394726 2.4588828336505686 2.0693403411656619 2.9026272313218215 2.5783995324105491 5.4993536350026258 2.4736523454863346 4.2446331617044049 1.8764321948197904 4.2502707783001821
5.0840524335741062 4.4030024509425854 1.6400465637503658 6.4004832592559975 3.6791089013946476 3.9198121311870637 4.1274743279587707 3.3353070575118182 3.2786815763189225 3.2441311231537839 3.2535645158874105 5.199402282357914 5.281745886293356 4.3296535222340022 4.6425480076664822 2.6515938470198308 3.4188237959257095 3.9721818592966884 1.2641333041188774 6.1579749098542376 6.4025937417114616 1 3.6338166336805444 5.3400354017299829 3.7376013478366077 5.6347801245807201 Q2 2013 4.3325643203628719 4.7253575742855904 1.6261836647812742 4.205002231471008 6.8870843718526888 0.92273817092645904 5.2676703929377258 0.9 3.8496963027922901 5.0034296676371017 3.5156336692365584 5.1965592759428549 5.1282537227292782 5.2852813935955059 1 2.1758940859639551 4.554598807159346 2.1334770720626692 5.241364395557321 4.0773214535205629 4.0392099875374701 5.0861743587360255 7.6592344597214836 4.6470289347111251 0.9 2.0076011863478924 1.3415140968631021 8.0482562664896253 4.913553401207901 5.0573001756914895 3.2576159340591402 4.263339950126829 1.6992101776180788 2.2969732966215815 5.3534252841258425 2.3312703418254386 3.6666470790136372 4.7275287655123979 1.0453071339055895 2.6700355177366872 4.1573383426351942 0.9 3.5076733168592908 5.9505744942056484 2.0504684001265558 8.2124891817569736 2.5168079431081423 3.9860188720253062 2.5933316904469392 1.3390093484544194 Q3 2013 3.7146412572171541
2.5241054166387769 2.6896680131601172 3.4734687281586232 5.121887857355178 1 3.4443303369032221 6.0388986233435578 2.5292204148415478 2.3882014423422517 3.2575328580848875 4.6841771612223244 3.5920977600896733 1.0686919770948591 2.8610331858787688 4.4406181180663413 4.8667564036138362 6.7562134566530592 2.8361203070078047 1.2506345731951298 3.4268334778305145 2.9840077834948899 4.6549896572530276 2.658026692485437 4.9887814887613064 3.7590027707908304 3.1200700098695235 2.1182925186865034 4.3161646820651374 3.6110861904732885 4.020589817925357 2.6307855071779342 4.4749861038569367 4.1842934072762734 4.72942270364612 4 2.646999978721142 2.3632449077256026 3.6397843862930315 5.6180936147272593 0.9 6.4001208150573081 3.2102573234867307 3.5474379322538154 5.9302431103121496 5.5190132619161165 4.9623297448549426 4.8508693501632667 5.5698431018088019 4.817243512049318 3.1770789567660542 Q4 2013 4.4392094297145377 4.0731587306290749 5.112268023462093 3.4856877947313478 4.6882091838633642 6.3605414298799587 8.2577867134241387 1.9114045345340855 8.9296140787191689 6.8537110665638465 5.687837084318744 3.0470982993429061 5.9130352484353352 1 1.8187038323085289 3.7439606431726133 6.1054524950159248 4.7754579200991429 4.1273587031391799 7.174651283188723 5.7005295376293361 1 3.3979271266653086 2.0414006586215692 4.3706494453581399 2.4660232712485595 3.2023929280549055
5.833204123613541 3.9361662048613653 2.4685073286527768 3.8865800989733543 6.875510290323291 1.7119800860236865 6.3871489247540012 6.5707099666760769 4.1814614734030329 8.8249639803543687 3.3480947750867927 5.499761538070743 6.5071526579267811 0.9 2.8718966505985009 7.4505069379520137 3.4878651250473922 3.0321399536696845 7.4588620110298507 4.844769601826556 2.8833146744582336 0.95167707614018582 3.0501850106738857 Q1 2014 2.7456040207704064 3.2393556203765912 4.3539226190710902 5.5837254386511628 2.894123937135737 5.0948083718190897 2.3263553849625169 1.6863519214035478 3.8792584710841767 3.3915317054430489 5.1440984371816736 0.98274408274446623 2.3405503235204379 2.8036798049521168 3.0573333298030776 2.4015251220640494 1.5885425874381327 3.0502597347600386 1.5024861987563782 5.5816790755721737 3.1106598463389674 1.0826270646299236 3.6316638862495894 1.8572607551555849 1.8951628099835944 6.0711554816458371 1 1 1.1885672812291888 3.7861455403850415 5.8584701456362378 0.9 2.2395776532954188 0.9 3.8749611086182996 2.464285372394079 3.8408806368403021 2.429744468923309 1.5390717600035715 0.9 3.6867980235052529 1.7277737207274186 3.5219481297695894 2.2330224702323904 5.3514018382935316 5.1112406673433721 6.4554624678799879 5.6095641831285317 3.6320509899320315 3.8695416570641101 Q2 2014 3.4465603756718339 1.95467528909212 2.7691193817037858 1.830401933041867 3.7153588062967176
4.588204054819653 1.1652720867306927 1.4585909492627254 1.8973007253254766 2.954022155684652 4.6879442460369321 3.3438613708160121 3.5946013293898433 4.0304668881464751 2.3857898749003654 1.6263281476160047 2.3982745086716024 4.4406580935930835 4.9579172890691554 4.4146033441240435 3.3970261109818241 3.1488661615032472 4.8728326954762453 3.969714915804798 3.8509883405669827 2.8099522832082586 1.7614722390891986 5.5786442397977227 4.9162933545478156 2.6285494722134901 3.2720810930943118 2.8562667092803169 3.8348668648570312 1.7931613082357218 2.7003026924678126 3.6135908966418357 0.9 3.3844030066422421 4.3807401278929321 2.872878402634524 2.1136076692375356 2.8578058016893921 3.1247515916067643 1.8599295880296269 2.4143211784423331 2.97 56362972722856 0.9 1.0139794620801696 4.5589501577371268 5.6660748749738561 Q3 2014 1.6701319585336023 2.5849427136818122 3.4712812824436696 3.1168675112239725 1 5.3960551516211126 3.895330913408543 4.4883640915286378 2.0577209700859385 4.4860002011118922 3.5669281790687819 3.4085343334736535 3.3083657134084206 2.7882290472261957 2.0893796280033712 4.2785482113031321 4.4665714616057812 1.9354151921361336 3.8966397899712319 3.3183290004926675 2.1960299894344644 3.5221082233219931 2.3136046896324842 1 5.8955778361705597 1.0873686808990897 4.5958403309923597 3.5192415528654237 4.1415744438636466 4.1337970136082731 2.4295045553371892
2.3373820643682848 2.5318425476398261 4.1416370853112312 2.6456999724614434 3.211152780593693 3.85011697592563 2.202989783952944 4.573015765643504 2.9913637225290586 4.1850706869154237 3.0259632315646741 1.9018393762307824 2.0914913041706313 1.0339421199460048 2.9528837406614912 7.4192420318722725 3.7933836059237365 2.4752080851867504 2.7128647919453215 Q4 2014 2.5510757682699476 2.3031384176196297 1.0432483764365315 1.5865764185495208 3.1144282689187093 4.0469112450868128 3.3778203219757414 1.2557568157266359 0.9 2.3109832641697721 2.7098836613280581 1.6538044479151721 3.5820508815508219 2.9565219124837312 3.7752575695325503 2.8747584524811827 0.90147952555562361 4.8724379853869326 3.1082047103613148 0.9 3.5162579211377305 3.1823331897161551 0.9 1.3526853040733839 1.6183518896927125 1.8669454407703596 1.0325304361234884 2.31182863949507 1.9896637882542563 3.9689445844036526 1 3.5086081612011184 2.410366592403443 2.4695753796098869 4.0189783890586117 2.0281505344886681 3.6200026175269158 4.1219250038469912 1.4048089001793413 2.4852340362034737 2.6676015937031479 4.3273157376010207 1.9502917626145062 2.7026329421918489 1.758633944109897 2.6436946159723447 4.4879045349720403 1.6248547768103889 1.1000000000000001 4.4970204003679104
From the data in this line graph, on response time between quarters, we are able to determine that there is no correlation between response times and quarters from how the lines on the graph are random. Part 2 - Shipping CostUnit Shipping Cost PlantExisting /ProposedCustomerMowersTractorsPlantExisting /ProposedKansas CityExistingToronto$1.36$1.79Kansas CityExistingSantiagoExistingToronto$1.49$2.13SantiagoExistin gKansas CityExistingShanghai$1.58$2.13AucklandProposedSantiagoExis tingShanghai$1.47$2.03BirminghamProposedKansas CityExistingMexico City$1.32$1.76FrankfurtProposedSantiagoExistingMexico City$1.22$1.58MumbaiProposedKansas CityExistingMelbourne$1.72$2.34SingaporeProposedSantiagoE xistingMelbourne$1.49$1.80Kansas CityExistingLondon$1.49$1.86SantiagoExistingLondon$1.58$2. 14Kansas CityExistingCaracas$1.54$1.90SantiagoExistingCaracas$1.00$1 .26Kansas CityExistingAtlanta$1.31$1.82SantiagoExistingAtlanta$1.31$1. 76SingaporeProposedToronto$1.71$2.03BirminghamProposedT oronto$1.34$1.78MowersTactorsFrankfurtProposedToronto$1.5 2$1.87QuartilesExistingProposedExistingProposedMumbaiProp osedToronto$1.67$2.14125%$ 1.31$ 1.77$ 1.40$ 1.78AucklandProposedToronto$1.86$2.19250%$ 1.48$ 1.84$ 1.52$ 2.01SingaporeProposedShanghai$1.44$1.78375%$ 1.53$ 2.11$ 1.66$ 2.17BirminghamProposedShanghai$1.60$2.154100%$ 1.72$ 2.34$ 1.98$ 2.68FrankfurtProposedShanghai$1.65$ 2.32MumbaiProposedSha nghai$1.21$1.47AucklandProposedShanghai$1.18$1.63Singapor eProposedMexico City$1.72$2.09BirminghamProposedMexico City$1.29$1.79FrankfurtProposedMexico
City$1.54$2.04MumbaiProposedMexico City$1.56$2.22AucklandProposedMexico City$1.50$2.07SingaporeProposedMelbourne$1.43$1.70Birming hamProposedMelbourne$1.52$2.06FrankfurtProposedMelbourne $1.73$2.28MumbaiProposedMelbourne$1.38$1.63AucklandProp osedMelbourne$0.91$1.17SingaporeProposedLondon$1.88$2.68 BirminghamProposedLondon$1.47$1.77FrankfurtPr oposedLond on$1.37$1.64MumbaiProposedLondon$1.44$1.82AucklandProp osedLondon$1.98$2.60SingaporeProposedCaracas$1.50$2.01Bir minghamProposedCaracas$1.37$1.86FrankfurtProposedCaracas $1.59$1.88MumbaiProposedCaracas$1.61$2.08AucklandPropos edCaracas$1.54$1.98SingaporeProposedAtlanta$1.73$2.35Birmi nghamProposedAtlanta$1.02$1.25FrankfurtProposedAtlanta$1.4 2$1.70MumbaiProposedAtlanta$1.57$2.23AucklandProposedAtl anta$1.74$2.26 You can see in the table of quartiles with Mowers and Tactors in Existing and Proposed shipping cost locations that Mowers have a slight increase in shipping costs in the proposed then the existing. There is also an increase in shipping cost in Tactors in Proposed locations compared to Existing locations. Fixed CostFixed Costs of Capacity Increase or New ConstructionCurrent PlantsAdditional CapacityCostKansas City10000$605,000.00Kansas City20000$985,000.00Santiago5000$381,000.00Santiago10000$ 680,000.00Proposed LocationsMaximum capacityCostAuckland15,000$917,000.00Auckland20,000$1,136 ,000.00Birmingham15,000$962,000.00Birmingham20,000$1,18 0,000.00Frankfurt15,000$874,000.00Frankfurt20,000$1,093,000 .00Mumbai15,000$750,000.00Mumbai25,000$959,000.00Singap ore15,000$839,000.00Singapore20,000$1,058,000.00 Part 3 - Regions and AveragesRow LabelsAverage of Ease of UseAverage of QualityAverage of PriceAverage of ServiceChina4.103.803.002.60Eur4.334.103.903.87NA4.274.60 3.714.31Pac3.904.404.104.30SA3.924.283.504.24Grand Total4.174.403.674.14 part 3 Row LabelsAverage of PriceAverage of ServiceAverage
of Ease of UseAverage of QualityChina32.64.13.8Eur3.93.86666666674.33333333334.1N A3.714.314.274.6Pac4.14.33.94.4SA3.54.243.924.28Grand Total3.674.144.1654.395 Average of Price China Eur NA Pac SA 3 3.9 3.71 4.0999999999999996 3.5 Average of Service China Eur NA Pac SA 2.6 3.8666666666666667 4.3099999999999996 4.3 4.24 Average of Ease of Use China Eur NA Pac SA 4.0999999999999996 4.333333333333333 4.2699999999999996 3.9 3.92 Average of Quality China Eur NA Pac SA 3.8 4.0999999999999996 4.5999999999999996 4.4000000000000004 4.28 Q1Anova: Single FactorSUMMARYGroupsCountSumAverageVarianceQuality200 8794.3950.5818844221Ease of Use2008334.1650.6108291457Price2007343.671.1367839196A NOVASource of VariationSSdfMSFP-valueF critBetween Groups54.9033333333227.451666666735.353118191403.01081 52042Within Groups463.575970.7764991625Total518.4733333333599 Part 3 - 2014 Customer Survey2014 Customer SurveyQuartiles RegionQualityEase of UsePriceServiceNorth AmericaSouth AmericaEuropePacific RimChinaNA4134QualityEase of UsePriceServiceQualityEase of UsePriceServiceQualityEase of UsePriceServiceQualityEase of UsePriceServiceQualityEase of UsePriceServiceNA444500%111200%111100%231100%323300 %2321NA4543125%4434125%4434125%4443.25125%3233125 %3.25432NA5444250%5444250%4444250%4444250%4444250 %4433NA5454375%554.255375%5445375%5554.75375%4.544 4375%4433NA55354100%55554100%55554100%55554100%54 454100%5544NA5442NA5545NA4445NA4545NA4514NA5544
Frequency DistrbutionNA5433North AmericaSouth AmericaEuropePacific Rim ChinaNA4544ValueQualityEase of UsePriceServiceValueQualityEase of UsePriceServiceValueQualityEase of UsePriceServiceValueQualityEase of UsePriceServiceValueQualityEase of UsePriceServiceNA54351125011121100211000010001NA55252 0210320180210122010021023NA5425336198346106363453111 132165NA54254304741444243523224121414144467545721NA 4544566432545521772151113985522452200NA4454NA4424N A4334NA5525NA5343NA5445NA5525NA5553NA4454NA5444 NA5155NA5435NA4514NA4435NA5344NA5524NA5444NA55 44NA5545NA4335NA5443NA5434NA5515NA5454NA3434NA 5424NA5545NA5534NA5444NA5444NA5445NA5414 NA5455N A5534NA5445NA4355NA5444Q1NA5555NA5545Anova: Single FactorNA4444NA5455SUMMARYNA4554GroupsCountSumAv erageVarianceNA5554Quality2008794.3950.5818844221NA553 5Ease of Use2008334.1650.6108291457NA5444Price2007343.671.13678 39196NA5452NA4455NA4445ANOVANA5444Source of VariationSSdfMSFP-valueF critNA5435Between Groups54.9033333333227.451666666735.353118191403.01081 52042NA5454Within Groups463.575970.7764991625NA5545NA5444Total518.47333 33333599NA5452NA5345NA5455NA5415NA4535NA3525NA5 544NA4435NA3245NA1434NA4535NA5544NA4555NA5545N A5544NA4245NA5454NA5454NA5543NA5555NA4553NA5545 NA4455NA5534NA4524NA5554NA4543NA4554SA5435SA542 4SA5455SA4245SA5445SA4525SA5444SA4535SA4443SA4424 SA5434SA3355SA5434SA5425SA4434SA4435SA1534SA5424S A4444SA4455SA5424SA4455SA4443SA3345SA5444SA4441S A4555SA4145SA4544SA4445SA5434SA4445SA5543SA5544S A4424SA4445SA5445SA5444SA5414SA3445SA4354SA4423S A5433SA4345SA5355SA5444SA5444SA3434SA4414SA4343Eu r4553Eur4442Eur3454Eur3413Eur4455Eur5555Eur5551Eur4554
Eur3444Eur3533Eur4454Eur5455Eur5344Eur5545Eur3444Eur4 545Eur4544Eur5445Eur4544Eur3534Eur4442Eur5534Eur5345E ur4524Eur4344Eur5433Eur2444Eur5454Eur4543Eur5415Pac544 5Pac5555Pac4444Pac4344Pac5454Pac4444Pac5545Pac4233Pac 3444Pac5445China5544China5543China4433China4433China44 32China4433China4432China3433China3422China2321 North America 1 Quality Ease of Use PriceService 1 2 5 0 2 Quality Ease of Use PriceService 0 2 10 3 3 Quality Ease of Use PriceService 3 6 19 8 4 Quality Ease of Use PriceService 30 47 41 44 5 Quality Ease of Use PriceService 66 43 25 45 South America 1 Quality Ease of Use PriceService 1 1 2 1 2 Quality Ease of Use PriceService 0 1 8 0 3 Quality Ease of Use PriceService 4 6 10 6 4 Quality Ease of Use PriceService 24 35 23 22 5 Quality Ease of Use PriceService 21 7 7 21 Europe 1 Quality Ease of Us e PriceService 0 0 2 1 2 Quality Ease of Use PriceService 1 0 1 2 3 Quality Ease of Use PriceService 6 3 4 5 4 Quality Ease of Use PriceService 12 14 14 14 5 Quality Ease of Use Price Service 11 13 9 8
Pacific Rim 1 Quality Ease of Use PriceService 0 0 0 0 2 Quality Ease of Use PriceService 0 1 0 0 3 Quality Ease of Use PriceService 1 1 1 1 4 Quality Ease of Use PriceService 4 6 7 5 5 Quality Ease of Use PriceService 5 2 2 4 China 1 Quality Ease of Use PriceService 0 0 0 1 2 Quality Ease of Use PriceService 1 0 2 3 3 Quality Ease of Use PriceService 2 1 6 5 4 Quality Ease of Use PriceService 5 7 2 1 5 Quality Ease of Use PriceService 2 2 0 0 In this chart with the frequency distribution for North America, you can see that the quality, ease of use, and service production areas don't need to really change anything. Those areas can do the same thing they are doing. The price section in this chart needs improvment in their pricing, by the wide variation in the distribution, you can reduce costs or use different materials. In this chart with the frequency distribution for South America, you can see that quality and service areas don't need to change anything they can keep on doing what they are doing. The ease of use can improve in turing all of those 4's into 5's for better ratings. Price again can change by reducing costs or changing
materials to reduce the pricing. In this chart with the frequency distribution shown in a historgram for Europe region, you can see all areas; quality, ease of use, price, and service all need improvments to get higher ratings from consumers. Price can reduce costs. Service can train their service workers to help customers better. Ease of use can improve the design of the product. Quality can improve on the procurment side to making better products. In this chart with the frequency distribution shown in a histogram for Pacific Rim region, you can see most of the areas most rated number is 4's. So, service, price, and ease of use can improve a little bit to make some of those 4's into 5's. Quality can improve the overall quality in products from the procurment side. In this chart showning the China regions distribution between areas and ratings. All areas need improvment to make the customers want to get these products again. Quality needs to improve the quality of the product by changing the procument side of things. Ease of use comes from that if the quality is good and making it easy to use will follow a little. We need to train or hire more people to help with the companies customer service so our customers have a good experience with our company. Overall everything is connected so if you focus on some areas the others will some what follow. Unit Production CostsUnit Production CostsMonthTractorMowerJan-10$1,750$1$50$1Feb- 10$1,755$1$50$1Mar-10$1,763$1$51$1Apr- 10$1,770$1$51$1May-10$1,778$1$51$1Jun- 10$1,785$1$51$1Jul-10$1,792$1$51$1Aug- 10$1,795$1$51$1Sep-10$1,801$1$52$1Oct- 10$1,804$1$52$1Nov-10$1,810$1$52$1Dec- 10$1,813$1$52$1Jan-11$1,835$1$55$1Feb- 11$1,841$1$55$1Mar-11$1,848$1$55$1Apr- 11$1,854$1$55$1May-11$1,860$1$56$1Jun- 11$1,866$1$56$1Jul-11$1,872$1$56$1Aug- 11$1,878$1$56$1Sep-11$1,885$1$56$1Oct-
11$1,892$1$57$1Nov-11$1,897$1$57$1Dec- 11$1,903$1$57$1Jan-12$1,925$1$59$1Feb- 12$1,931$1$59$1Mar-12$1,938$1$59$1Apr- 12$1,944$1$59$1May-12$1,950$1$59$1Jun- 12$1,956$1$60$1Jul-12$1,963$1$60$1Aug- 12$1,969$1$60$1Sep-12$1,976$1$60$1Oct- 12$1,983$1$60$1Nov-12$1,990$1$61$1Dec- 12$1,996$1$61$1Jan-13$1,940$1$59$1Feb- 13$1,946$1$59$1Mar-13$1,952$1$59$1Apr- 13$1,958$1$59$1May-13$1,964$1$60$1Jun- 13$1,970$1$60$1Jul-13$1,976$1$60$1Aug- 13$1,983$1$60$1Sep-13$1,990$1$60$1Oct- 13$1,996$1$60$1Nov-13$2,012$1$61$1Dec- 13$2,008$1$61$1Jan-14$2,073$1$63$1Feb- 14$2,077$1$63$1Mar-14$2,081$1$63$1Apr- 14$2,086$1$63$1May-14$2,092$1$63$1Jun- 14$2,098$1$63$1Jul-14$2,104$1$64$1Aug- 14$2,110$1$64$1Sep-14$2,116$1$64$1Oct- 14$2,122$1$64$1Nov-14$2,129$1$64$1Dec- 14$2,135$1$64$1$1,938$58 Tractor 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 1750 1755 1763 1770 1778 1785 1792 1795 1801 1804 1810 1813 1835 1841 1848 1854 1860 1866 1872 1878 1885 1892 1897 1903 1925 1931 1938 1944 1950 1956 1963 1969 1976 1983 1990 1996 1940 1946 1952 1958 1964 1970 1976 1983 1990 1996 2012 2008 2073 2077 2081 2086 2092 2098 2104
2110 2116 2122 2129 2135 Mower 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 50 50 51 51 51 51 51 51 52 52 52 52 55 55 55 55 56 56 56 56 56 57 57 57 59 59 59 59 59 60 60 60 60 60 61 61 59 59 59 59 60 60 60 60 60 60 61 61 63 63 63 63 63 63 64 64 64 64 64 64 Items for 2014 Income StatementRevenuePerformance Lawn EquipmentMowers revenue1,161,069.16Income Statement for the year ending December 2014Tractors Revenue281,736.21$$Total Revenue1,442,805.38RevenueMowers revenue1,161,069.16Tractors revenues281,736.21Total Revenue1,442,805.38ExpensesAdministrative 7,738,943.00ExpensesDepreciation2,486,977.00Administrative 7,738,943.00Interest117,855.00Depreciation2,486,977.00Selling Expense259,704.97Interest117,855.00Tax ExpenseSelling Expense259,704.97Total Expenses10,603,479.97Gross profit/loss(9,160,674.59)Tax (50%)(4,580,337.30)Net
loss(4,580,337.30)Performance Lawn EquipmentPro forma Income Statement for the year ending December 2014$$$As ReportedPro forma adjustmentsPro formaRevenueMowers revenue1,161,069.16- 01,161,069.16Tractors revenues281,736.21- 0281,736.21Total Revenue1,442,805.38- 01,442,805.3818.6434423505ExpensesAdministrative 7,738,943.00- 07,738,943.00Depreciation2,486,977.00- 02,486,977.00Interest117,855.00- 0117,855.00Selling Expense259,704.97(259,704.97)0Total Expenses10,603,479.97259,704.9710,343,775.00Gross profit/loss(9,160,674.59)(8,900,969.62)Tax (50%)(4,580,337.30)(4,450,484.81)Net loss(4,580,337.30)(259,704.97)(4,450,484. 81) Operating & Interest ExpensesOperating and Interest ExpensesMonthAdministrativeDepreciationInterestJan- 10$633,073$140,467$7,244Feb-10$607,904$165,636$7,679Mar- 10$630,687$142,853$6,887Apr- 10$613,401$160,139$6,917May- 10$607,664$165,876$8,316Jun-10$632,967$140,573$7,428Jul- 10$609,604$163,936$8,737Aug- 10$607,749$165,791$7,054Sep-10$603,367$170,173$8,862Oct- 10$629,083$144,457$8,488Nov- 10$611,995$161,545$7,049Dec- 10$625,712$147,828$8,807$1,869,274Jan- 11$656,123$175,447$7,430Feb-11$652,679$178,891$6,791Mar- 11$655,521$176,049$8,013Apr- 11$676,581$154,989$8,979May- 11$676,581$154,989$7,484Jun-11$656,440$175,130$7,858Jul- 11$661,969$169,601$7,424Aug- 11$677,212$154,358$6,848Sep-11$653,545$178,025$6,751Oct- 11$657,388$174,182$8,160Nov- 11$672,475$159,095$7,898Dec- 11$656,325$175,245$8,953$2,026,001Jan- 12$723,594$226,526$9,443Feb-12$759,042$191,078$8,464Mar- 12$749,187$200,933$10,264Apr- 12$751,499$198,621$8,547May-
12$741,452$208,668$8,578Jun-12$729,122$220,998$9,519Jul- 12$734,783$215,337$9,343Aug- 12$748,208$201,912$8,448Sep-12$738,186$211,934$9,957Oct- 12$759,403$190,717$9,738Nov- 12$726,183$223,937$9,785Dec- 12$757,037$193,083$8,191$2,483,744Jan- 13$672,232$179,138$9,914Feb-13$665,023$186,347$9,954Mar- 13$667,657$183,713$10,859Apr- 13$654,198$197,172$9,730May- 13$659,435$191,935$10,430Jun- 13$661,190$190,180$10,222Jul- 13$647,321$204,049$10,102Aug- 13$666,743$184,627$10,610Sep- 13$678,705$172,665$9,374Oct- 13$658,990$192,380$10,830Nov- 13$656,221$195,149$9,017Dec- 13$676,934$174,436$10,423$2,251,791Jan- 14$641,571$210,589$9,985Feb-14$634,973$217,187$9,766Mar- 14$662,054$190,106$11,148Apr- 14$654,962$197,198$9,339May- 14$645,579$206,581$9,468Jun-14$658,112$194,048$10,324Jul- 14$637,711$214,449$9,737Aug- 14$638,317$213,843$9,290Sep-14$651,996$200,164$9,213Oct- 14$630,766$221,394$10,143Nov- 14$645,095$207,065$10,383Dec- 14$637,807$214,353$9,059$2,486,977Jan- 14$641,571$210,589$9,985Feb-14$634,973$217,187$9,766Mar- 14$662,054$190,106$11,148Apr- 14$654,962$197,198$9,339May- 14$645,579$206,581$9,468Jun-14$658,112$194,048$10,324Jul- 14$637,711$214,449$9,737Aug- 14$638,317$213,843$9,290Sep-14$651,996$200,164$9,213Oct- 14$630,766$221,394$10,143Nov- 14$645,095$207,065$10,383Dec- 14$637,807$214,353$9,059Total expenses$7,738,943$2,486,977$117,855
Growth PredictionIndustry Mower Total SalesPerformance Lawn Equipment MonthNASAEurPacWorldchange% changeIncome statementJan- 1060000157111309111045174,662.34Historic ResultsForecast PeriodFeb- 1077184161111767911111196,585.262014201520162017Mar- 10778851658122759110681102,369.09$$$$Apr- 10861901778127966112371116,171.47RevenueMay- 10961171886127895113131126,210.09Mowers revenue1,161,069.161,164,610.421,200,023.031,236,623.74Jun- 10971431882130566111761129,767.72Tractors revenues281,736.21318,643.66360,385.98407,596.54Jul - 10847571848129444113591116,409.43Total Revenue1,442,805.381,483,254.081,560,409.011,644,220.28Au g-10798041735128364112381110,140.95Sep- 1064800165712839311215195,064.95ExpensesOct- 1059307159512444411154185,499.82Administrative 7,738,943.008,512,837.309,364,121.0310,300,533.13Nov- 1052157155311800011262171,971.63Depreciation2,486,977.00 2,611,325.852,741,892.142,878,986.75Dec- 1045049146211245311386159,349.05Interest117,855.00117,855 .00117,855.00117,855.001,184,201.80Total Expenses10,343,775.0011,242,018.1512,223,868.1713,297,374. 88Jan-1158627155311277811443173,401.16Feb- 1176200161511821411515196,544.82Gross profit/loss(8,900,969.62)(9,758,764.07)(10,663,459.16)(11,653, 154.61)Mar-11828711658123889113731108,790.62Tax (50%)(4,450,484.81)(4,879,382.03)(5,331,729.58)(5,826,577.30 )Apr-11849041784129455114421116,584.48Net loss(4,450,484.81)(4,879,382.03)(5,331,729.58)(5,826,577.30) May-11931001846129464112151124,625.39Jun- 11930001838127414113331122,584.96Jul- 11830481763127368114151112,594.29Aug- 11748541694127321112961104,164.40What if the administrative expenses are reduced by 80% and depreciation by 40% for the next three years?Sep-
1160769162512944411402192,240.54Oct- 1155619161012377411468181,470.28Nov- 1148155157111730811351167,385.81Performance Lawn Equipment Dec-1142647151211294111389157,489.32Income statement1,157,876.09Historic ResultsForecast Period2014201520162017Jan- 1257885153711096211509170,892.17$$$$Feb- 1277647159511527311402194,916.89RevenueMar- 12818451659120556115241104,582.56Mowers revenue1,161,069.161,164,610.421,200,023.031,236,623.74Apr - 12860951756126786115741115,211.12Tractors revenues281,736.21318,643.66360,385.98407,596.54May- 12917761878124828114681118,949.23Total Revenue1,442,805.381,483,254.081,560,409.011,644,220.28Jun -121006801825124737115601127,801.09Jul- 12861901756124828114411113,215.60ExpensesAug- 1271887171412517911545199,325.10Administrative 7,738,943.001,547,788.60309,557.7261,911.54Sep- 1260000165112454511667186,863.28Depreciation2,486,977.00 1,492,186.20895,311.72537,187.03Oct- 1255566164311928611698177,192.72Interest117,855.00117,855 .00117,855.00117,855.00Nov- 1250857161911527311810168,558.44Total Expenses10,343,775.003,157,829.801,322,724.44716,953.58Dec -124259615481910701731153,981.681,131,489.90Gross profit/loss(8,900,969.62)(1,674,575.72)237,684.57927,266.70Ja n-135809515811857101887169,134.85Tax (50%)(4,450,484.81)(837,287.86)118,842.29463,633.35Feb- 1375566161411315811845191,182.23Net loss(4,450,484.81)(837,287.86)118,842.29463,633.35Mar - 13802861622119655119231102,486.19Apr- 13851401727125179119811113,027.16May- 13900931826123103118101115,831.65Jun- 13954721783124286119421122,481.77Tornado ChartJul- 13873081681124737119611114,686.17Aug- 13744761646126607120001103,729.17Sep-
1361698162512298212075187,381.04Oct- 1357238161711689712019176,770.90Nov- 1350673158711375012095167,105.27Dec- 135123815911781802150161,796.721,125,613.12(5,876.78)- 0.5220962393Jan-145971215631754701852169,673.06Feb- 1477961157111388911743194,164.60Mar- 14837251625118302118921104,544.27Apr- 14902971723125192120371118,249.78May- 14911431848124706118871118,583.36Jun- 14993201792125306119441127,362.62Jul- 14939221745127083121701123,919.39Aug- 14731431739126042120371101,960.69Sep- 1466699166712630412018195,688.39Oct- 1456476166012255812072181,765.98Nov- 1451068162511477312182168,647.51Dec- 144689316081697702035156,509.511,161,069.1635,456.043.05 37408648Industry Tractor Total SalesMonthNASAEurPacChinaWorldChange% ChangeJan- 10814319840509119871278015,485.83Feb- 1085921105115310110901283016,328.18Mar- 1086301101606071111271285017,132.35Apr- 1089471102705856112091288017,330.62May- 1084421105715273112211286016,280.89Jun- 1075001101905315113271287015,451.48Jul- 106145197707170113241289015,908.41Aug- 1058821105715926112681290014,425.63Sep- 1055951108616075112091293014,261.55Oct- 1052331104506321111681295014,064.35Nov- 1044941107818381111271298015,381.41Dec- 1039131102907944110851301014,275.34186,326.04Jan- 1159381117215688111851306014,291.68Feb- 1166331127317037112861302016,533.66Mar- 1173271142316981112861303017,323.62Apr- 1180771161217500113461307018,845.80May- 1178301172816571113881309017,830.03Jun- 1171031181516990114491312017,673.15Jul-
1162391177616667114901315016,490.40Aug- 1160361168516762114491318016,253.93Sep- 1156641167916635113941321015,696.01Oct- 1153451161816311112561315014,847.59Nov- 1148311156416476112141318014,405.22Dec- 1144541152216250111711320013,719.41193,910.51Jan- 1252991183515922112081333014,600.47Feb- 1265291211516667112141313016,840.19Mar- 1271201220217228112561606118,416.03Apr- 1276191215118200113111571119,855.97May- 1283871221417941114151556120,517.20Jun- 1281101227817921115201526020,359.05Jul- 1277521210017677116751513019,720.51Aug- 1268941212817200115841769118,579.21Sep- 1260151236716735115271750117,398.43Oct- 1253681221116495114221732116,230.13Nov- 1249641248316061113661714115,591.09Dec- 1244441198615816112621698114,210.03212,318.31Jan- 1350001225715051113731714114,397.83Feb- 13628412353160821143611063117,221.81Mar- 13778512457163271147811264119,314.63Apr- 13993412517176041151211333122,905.96May- 131064512612177891164211556124,248.74Jun- 13949112749173471166711739222,997.82Jul- 13918212887169791173311702222,487.92Aug- 13852812833164891170011915221,469.38Sep- 13829312789163161164212083221,127.34Oct- 13822112765158331157612128220,527.19Nov- 13747012746157891149312292219,793.63Dec- 13650912534155911145012245218,332.97244,825.22Jan- 14726712635151061101012292218,314.48Feb- 14880712703154741104512449220,481.03Mar- 141016812795160221110612400222,493.67Apr- 141104412997160641115012353223,612.03May- 141212023131163441124412600225,443.74Jun- 141345923311265931135712653227,378.90Jul-
141304823390263041142112600226,768.99Aug- 141227523277260641126312549225,432.69Sep- 141134713232257891117312453224,000.05Oct- 141066713131156991112812517223,146.72Nov- 14104591308715604197412541222,670.62Dec- 14100821303015444197912453221,993.30281,736.2136,910.99 13.1012595342 Tornado Chart -4450484.811629016 -4879382.0341685694 - 5331729.5811128728 -5826577.3034424353 -4450484.811629016 -837287.85916856956 118842.28513712832 463633.34987006639 Industry Mower Total SalesIndustry Mower Total SalesMonthNASAEurPacWorldJan- 10600001571113091110451746621Feb- 10771841611117679111111965851Mar- 107788516581227591106811023691Apr- 108619017781279661123711161711May- 109611718861278951131311262101Jun- 109714318821305661117611297681Jul- 108475718481294441135911164091Aug- 107980417351283641123811101411Sep- 10648001657128393112151950651Oct- 10593071595124444111541855001Nov- 10521571553118000112621719721Dec- 10450491462112453113861593491Jan- 11586271553112778114431734011Feb- 11762001615118214115151965451Mar- 118287116581238891137311087911Apr-
118490417841294551144211165841May- 119310018461294641121511246251Jun- 119300018381274141133311225851Jul- 118304817631273681141511125941Aug- 117485416941273211129611041641Sep- 11607691625129444114021922411Oct- 11556191610123774114681814701Nov- 11481551571117308113511673861Dec- 11426471512112941113891574891Jan- 12578851537110962115091708921Feb- 12776471595115273114021949171Mar- 128184516591205561152411045831Apr- 128609517561267861157411152111May- 129177618781248281146811189491Jun- 1210068018251247371156011278011Jul- 128619017561248281144111132161Aug- 12718871714125179115451993251Sep- 12600001651124545116671868631Oct- 12555661643119286116981771931Nov- 12508571619115273118101685581Dec- 1242596154819107017311539821Jan- 1358095158118571018871691351Feb- 13755661614113158118451911821Mar- 138028616221196551192311024861Apr- 138514017271251791198111130271May- 139009318261231031181011158321Jun- 139547217831242861194211224821Jul- 138730816811247371196111146861Aug- 137447616461266071200011037291Sep- 13616981625122982120751873811Oct- 13572381617116897120191767711Nov- 13506731587113750120951671051Dec- 1351238159117818021501617971Jan- 1459712156317547018521696731Feb- 14779611571113889117431941651Mar- 148372516251183021189211045441Apr-
149029717231251921203711182501May- 149114318481247061188711185831Jun- 149932017921253061194411273631Jul- 149392217451270831217011239191Aug- 147314317391260421203711019611Sep- 14666991667126304120181956881Oct- 14564761660122558120721817661Nov- 14510681625114773121821686481Dec- 14468931608169770203515651017258167621120162896004Jan -145971215631754701852169673Feb- 1477961157111388911743194165Mar- 14837251625118302118921104544Apr- 14902971723125192120371118250May- 14911431848124706118871118583Jun- 14993201792125306119441127363Jul- 14939221745127083121701123919Aug- 14731431739126042120371101961Sep- 1466699166712630412018195688Oct- 1456476166012255812072181766Nov- 1451068162511477312182168648Dec- 144689316081697702035156510Total Revenue1,161,069.16 North America 40179 40210 40238 40269 40299 40330 40360 4039 1 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 60000 77184.466019417479 77884.61538461539 86190.476190476198 96116.504854368934 97142.857142857145 84757.281553398061 79803.921568627455 64800 59306.930693069306
52156.862745098042 45048.543689320388 58627.450980392161 76200 82871.287128712866 84903.846153846156 93100 93000 83047.619047619053 74854.368932038837 60769.230769230773 55619.047619047618 48155.339805825242 42647.058823529413 57884.61538461539 77647.058823529413 81844.660194174765 86095.238095238092 91775.700934579436 100679.61165048544 86190.476190476198 71886.792452830196 60000 55566.037735849059 50857.142857142862 42596.153846153851 58095.238095238099 75566.037735849066 80285.71428571429 85140.186915887854 90092.592592592599 95471.698113207545 87307.692307692312 74476.190476190473 61698.113207547169 57238.095238095237 50673.076923076922 51238.095238095237 59711.538461538461 77961.165048543699 83725.490196078434 90297.029702970292 91142.857142857145 99320.388349514571 93921.568627450994 73142.857142857145 66699.029126213602 56476.190476190481 51067.961165048546 46893.203883495145 South America 40179 40210 40238 40269 40299 40330 40360 4039 1 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609
41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 571.42857142857144 611.11111111111109 657.8947368421052 777.77777777777783 885.71428571428578 882.35294117647049 848.4848484848485 735.29411764705878 657.14285714285722 594.59459459459458 552.63157894736844 461.53846153846155 552.63157894736844 615.38461538461536 657.8947368421052 783.78378378378375 846.15384615384608 837.83783783783781 763.15789473684208 694 625 609.7560975609756 571.42857142857144 512.19512195121956 536.58536585365857 595.2380952380953 658.53658536585374 756.09756097560978 878.04878048780495 825 756.09756097560978 714.28571428571433 651.16279069767438 642.85714285714289 619.04761904761904 547.61904761904759 581.39534883720933 613.63636363636363 622.22222222222217 727.27272727272725 826.08695652173913 782.60869565217388 680.85106382978722 645.83333333333337 625 617.02127659574467 586.95652173913038 590.90909090909088 562.5 571.42857142857144 625 723.404255319149 847.82608695652175 791.66666666666674 744.68085106382978 739.13043478260863 666.66666666666674 659.57446808510645 625 608 Europe 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695
40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 13090.90909090909 17678.571428571428 22758.62068965517 27966.101694915254 27894.736842105263 30566.037735849059 29444.444444444445 28363.636363636364 28392.857142857141 24444.444444444445 18000 12452.830188679245 12777.777777777777 18214.285714285714 23888.888888888891 29454.545454545456 29464.285714285714 27413.793103448275 27368.421052631576 27321.428571428572 29444.444444444445 23773.584905660377 17307.692307692309 12941.176470588236 10961.538461538463 15272.727272727272 20555.555555555555 26785.714285714286 24827.586206896551 24736.842105263157 24827.586206896551 25178.571428571428 24545.454545454544 19285.714285714286 15272.727272727272 9107.1428571428569 8571.4285714285706 13157.894736842105 19655.172413793101 25178.571428571428 23103.448275862069 24285.714285714286 24736.842105263157 26607.142857142855 22982.456140350878 16896.551724137931 13750 7818.181818181818 7547.1698113207549 13888.888888888889 18301.886792452831 25192.307692307695 24705.882352941178 25306.12244897959 27083.333333333332 26041.666666666668 26304.347826086956 22558.139534883721 14772.727272727274 6976.7441860465124
Pacific 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 1045 1111.1111111111111 1067.9611650485438 1237.1134020618556 1313.1313131313132 1176.4705882352941 1359.2233009708739 1238.0952380952381 1214.9532710280373 1153.8461538461538 1262.1359223300972 1386.1386138613861 1443.2989690721649 1515.151515151515 1372.5490196078433 1442.3076923076924 1214.9532710280373 1333.3333333333335 1415.0943396226417 1296.2962962962963 1401.8691588785048 1467.8899082568807 1351.3513513513512 1388.8888888888889 1509.433962264151 1401.8691588785048 1523.8095238095239 1574.0740740740741 1467.8899082568807 1559.6330275229359 1441.4414414414414 1545.4545454545455 1666.6666666666667 1698.1132075471698 1809.5238095238096 1730.7692307692309 1886.7924528301887 1844.6601941747574 1923.0769230769231 1981.1320754716983 1809.5238095238096 1941.7475728155341 1960.7843137254904 2000 2075.4716981132078 2019.2307692307693
2095.2380952380954 2149.532710280374 1851.851851851852 1743.119266055046 1891.8918918918919 2037.037037037037 1886.7924528301887 1944.4444444444446 2169.8113207547171 2037.037037037037 2018.3486238532109 2072.0720720720719 2181.818181818182 2035.3982300884954 World 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 74662.337662337668 96585.259670211133 102369.09197616122 116171.4690652311 126210.0872953198 129767.71840811797 116409.43414729823 110140.94728800612 95064.953271028033 85499.815885954507 71971.630246375498 59349.050953399485 73401.159306189467 96544.821844821839 108790.61977405171 116584.48308448309 124625.39283146759 122584.96427461944 112594.2923346101 104164.4014920714 92240.544372553719 81470.278530525859 67385.812036297473 57489.31930495776 70892.173174271666 94916.89335037327 104582.56185890571 115211.12401600207 118949.22583022068 127801.08678327154
113215.6013997898 99325.104141141885 86863.28400281888 77192.722371967655 68558.441558441569 53981.684981684986 69134.854468334073 91182.229030502291 102486.1858448 0653 113027.1631472037 115831.65163450023 122481.76866738955 114686.16979051076 103729.16666666666 87381.041046011247 76770.899008059685 67105.271540054149 61796.718857466512 69673.060124711075 94164.601774916198 104544.26888042316 118249.77868763417 118583.35803558504 127362.62190960527 123919.39413260287 101960.69128134346 95688.392242820439 81765.976551231375 68647.506619594002 56509.512966296817 Industry Tractor Total SalesIndustry Tractor Total SalesMonthNASAEurPacChinaWorldJan- 108143198405091198712780154861Feb- 10859211051153101109012830163281Mar- 10863011016060711112712850171321Apr- 10894711027058561120912880173311May- 10844211057152731122112860162811Jun- 10750011019053151132712870154511Jul- 1061451977071701132412890159081Aug- 10588211057159261126812900144261Sep- 10559511086160751120912930142621Oct- 10523311045063211116812950140641Nov- 10449411078183811112712980153811Dec- 10391311029079441108513010142751Jan- 11593811172156881118513060142921Feb- 11663311273170371128613020165341Mar- 11732711423169811128613030173241Apr- 11807711612175001134613070188461May-
11783011728165711138813090178301Jun- 11710311815169901144913120176731Jul- 11623911776166671149013150164901Aug- 11603611685167621144913180162541Sep- 11566411679166351139413210156961Oct- 11534511618163111125613150148481Nov- 11483111564164761121413180144051Dec- 11445411522162501117113200137191Jan- 12529911835159221120813330146001Feb- 12652912115166671121413130168401Mar- 12712012202172281125616061184161Apr- 12761912151182001131115711198561May- 12838712214179411141515561205171Jun- 12811012278179211152015260203591Jul- 12775212100176771167515130197211Aug- 12689412128172001158417691185791Sep- 12601512367167351152717501173981Oct- 12536812211164951142217321162301Nov- 12496412483160611136617141155911Dec- 12444411986158161126216981142101Jan- 13500012257150511137317141143981Feb- 136284123531608211436110631172221Mar- 137785124571632711478112641193151Apr- 139934125171760411512113331229061May- 1310645126121778911642115561242491Jun- 139491127491734711667117392229981Jul- 139182128871697911733117022224881Aug- 138528128331648911700119152214691Sep- 138293127891631611642120832211271Oct- 138221127651583311576121282205271Nov- 137470127461578911493122922197941Dec- 136509125341559111450122452183331Jan- 147267126351510611010122922183141Feb- 148807127031547411045124492204811Mar- 1410168127951602211106124002224941Apr- 1411044129971606411150123532236121May-
1412120231311634411244126002254441Jun- 1413459233112659311357126532273791Jul- 1413048233902630411421126002267691Aug- 1412275232772606411263125492254331Sep- 1411347132322578911173124532240001Oct- 1410667131311569911128125172231471Nov- 141045913087156041974125412226711Dec- 14100821303015444197912453221993177262093643613231070 18652Jan-14726712635151061101012292218314Feb- 14880712703154741104512449220481Mar- 141016812795160221110612400222494Apr- 141104412997160641115012353223612May- 141212023131163441124412600225444Jun- 141345923311265931135712653227379Jul- 141304823390263041142112600226769Aug- 141227523277260641126312549225433Sep- 141134713232257891117312453224000Oct- 141066713131156991112812517223147Nov- 14104591308715604197412541222671Dec- 14100821303015444197912453221993281,736.21 North America 40179 40210 40238 40269 40299 40330 40360 40 391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 8142.8571428571422 8591.5492957746483 8630.1369863013697 8947.3684210526317 8441.5584415584417 7500 6144.5783132530123 5882.3529411764703 5595.2380952380954 5232.5581395348845 4494.3820224719102
3913.0434782608695 5937.5 6632.6530612244906 7326.7326732673273 8076.9230769230771 7830.1886792452833 7102.8037383177571 6238.5321100917436 6036.0360360360355 5663.716814159292 5344.8275862068958 4830.5084745762706 4453.7815126050418 5299.1452991452988 6528.9256198347121 7120 7619.0476190476193 8387.0967741935492 8110.2362204724404 7751.937984496124 6893.939393939394 6015.0375939849619 5367.6470588235288 4964.0287769784172 4444.4444444444443 5000 6283.7837837837833 7785.2348993288579 9934.21052631579 10645.161290322581 9491 9182.3899371069183 8527.6073619631898 8292.6829268292677 8220.8588957055217 7469.8795180722891 6508.8757396449701 7267.4418604651155 8806.8181818181802 10167.597765363127 11043.956043956043 12119.565217391304 13459.45945945946 13048.128342245989 12275.132275132275 11347.150259067357 10666.666666666666 10459.183673469388 10082 South America 40179 40210 40238 40269 40299 40330 40360 40 391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791
41821 41852 41883 41913 41944 41974 984 1050.5836575875487 1015.625 1026.6159695817489 1056.6037735849056 1018.8679245283018 977.4436090225563 1056.6037735849056 1086.1423220973782 1044.7761194029849 1078.0669144981412 1029.4117647058822 1172.1611721611721 1272.7272727272725 1423.3576642335765 1611.7216117216117 1727.9411764705881 1814.8148148148148 1776 1684.9816849816848 1678.8321167883209 1617.6470588235293 1563.6363636363635 1521.7391304347825 1834.5323741007192 2114.6953405017921 2202.1660649819491 2150.5376344086021 2214.2857142857142 2277.5800711743768 2099.6441281138787 2127.6595744680853 2367.4911660777389 2210.5263157894738 2482.5174825174827 1986.0627177700351 2256.9444444444448 2352.9411764705883 2456.7474048442909 2517.2413793103451 2611.6838487972509 2749.1408934707906 2886.5979381443299 2832.764505119454 2789.1156462585036 2764.5051194539251 2745.7627118644068 2533.7837837837837 2635.1351351351354 2702.7027027027029 2794.6127946127949 2996.6329966329968 3131.3131313131316 3310.8108108108108 3389.8305084745766 3277.0270270270271 3232.3232323232323 3131.3131313131316 3087.2483221476509 3030.3030303030305 Europe 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513
40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 5090.909090909091 5309.7345132743358 6071.4285714285716 5855.8558558558561 5272.727272727273 5315.3153153153153 7169.8113207547176 5925.9259259259261 6074.7663551401874 6320.7547169811323 8380.9523809523816 7943.9252336448599 5688.0733944954127 7037.0370370370374 6981.132075471698 7500 6571.4285714285716 6990.2912621359228 6666.666666666667 6761.9047619047624 6634.6153846153848 6310.6796116504856 6476.1904761904761 6250 5922.3300970873788 6666.666666666667 7227.7227722772286 8200 7941.176470588236 7920.7920792079212 7676.7676767676767 7200 6734.6938775510198 6494.8453608247419 6060.6060606060601 5816.3265306122448 5050.5050505050503 6082.4742268041236 6326.5306122448974 7604.16666 66666661 7789.4736842105258 7346.9387755102034 6979.166666666667 6489.3617021276596 6315.7894736842109 5833.333333333333 5789.4736842105267 5591.3978494623652 5106.3829787234044 5473.6842105263158 6021.5053763440865 6063.8297872340427 6344.0860215053763 6593.4065934065939 6304.347826086957 6063.8297872340427 5789.4736842105267 5698.9247311827958 5604.3956043956041 5444.4444444444443
Pacific 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 987 1090.0473933649289 1126.7605633802816 1209.3023255813953 1220.6572769953052 1327.0142180094788 1324.2009132420092 1267.605633802817 1209.3023255813953 1168.2242990654206 1126.7605633802816 1084.9056603773586 1184.8341232227488 1285.7142857142858 1285.7142857142858 1346.1538461538462 1387.5598086124403 1449.2753623188407 1490.3846153846155 1449.2753623188407 1394.2307692307693 1256.0386473429953 1213.5922330097087 1170.7317073170732 1207.7294685990339 1213.5922330097087 1256.0386473429953 1310.6796116504854 1414.6341463414635 1519.607843137255 1674.8768472906402 1584.158415841584 1527.0935960591132 1421.5686274509806 1365.8536585365855 1262.1359223300972 1372.5490196078433 1435.6435643564355 1477.832512315270 8 1512.1951219512196 1641.7910447761194 1666.6666666666667 1732.6732673267325 1700 1641.7910447761194 1576.3546798029556
1492.5373134328358 1450 1010.10101010101 1044.7761194029849 1105.5276381909548 1150 1243.7810945273632 1356.7839195979898 1421.3197969543146 1262.6262626262626 1173.4693877551019 1128.2051282051282 974.35897435897436 979.38144329896909 China 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 278 283 285 288 286 287 289 290 293 295 298 301 306 302 303 307 309 312 315 318 321 315 318 320 333.33333333333337 312.5 606.06060606060601 571.42857142857133 555.55555555555554 526.31578947368428 512.82051282051282 769.23076923076928 750 731.70731707317077 714.28571428571433 697.67441860465124 714.28571428571433 1063 1264 1333.3333333333335 1555.5555555555557 1739.1304347826087 1702.127659574468 1914.8936170212767 2083.3333333333335 2127.6595744680849 2291.666666 6666665 2244.8979591836733 2291.6666666666665 2448.9795918367345 2400 2352.9411764705883 2600 2653.0612244897957 2600 2549.0196078431372 2452.8301886792451 2517 2541 2452.8301886792451
World 40179 40210 40238 40269 40299 40330 40360 40391 40422 40452 40483 40513 40544 40575 40603 40634 40664 40695 40725 40756 40787 40817 40848 40878 40909 40940 40969 41000 41030 41061 41091 41122 41153 41183 41214 41244 41275 41306 41334 41365 41395 41426 41456 41487 41518 41548 41579 41609 41640 41671 41699 41730 41760 41791 41821 41852 41883 41913 41944 41974 15485.827364316103 16328.177768112695 17132.348420012986 17330.615077530954 16280.886107982882 15451.483910501687 15908.411398406914 14425.633349435642 14261.550181077717 14064.35482268759 15381.41255497461 14275.338779719703 14291.676593971913 16533.663433037509 17323.621594248918 18845.796830272586 17830.027142679752 17673.153172992101 16490.401766399569 16253.930247756805 15696.014975118776 14847.587500892381 14405.223401936522 13719.411885118465 14600.466025397956 16840.188427993337 18416.03421337191 19855.971854686119 20517.195307728711 20359.049234240487 19720.512435599452 18579.213122991761 17398.426601389649 16230.129230188584 15591.094371402309 14210.025912098807 14397.831903482002 17221.810489524978 19314 .626910507486 22905.96004813246 24248.74233614793 22997.820014039953 22487.917191375578
21469.377637268572 21127.340647579105 20527.194347858862 19793.626314204532 18332.973158006946 18314.484223735177 20481.032187050154 22493.666036040744 23612.032608397036 25443.736066418991 27378.895949558133 26768.988797130431 25432.686015877025 24000.046319474648 23146.724604316583 22670.622639347333 21993.298087858158 Q3Anova: Single FactorSUMMARYGroupsCountSumAverageVariance201012991 6826.3333333333135.333333333320111210049837.4166666667 121.53787878792012129431785.91666666672749.71969696972 013128029669.0833333333959.35606060612014125955496.252 940.0227272727ANOVASource of VariationSSdfMSFP-valueF critBetween Groups984600.3333333334246150.083333333178.2154383340. 00002.5396886349Within Groups75965.6666666667551381.1939393939Total106056659 Defects After DeliveryDefects After DeliveryDefects per million items received from suppliersMonth20102011201220132014January81282882468257 1February810832836695575March813847818692547April82383 9825686542May832832804673532June848840812681496July83 7849806696472August831857798688460September8278398046 71441October838842713645445November826828705617438Dec ember819816686603436Total 991610049943180295955Q3Anova: Single FactorSUMMARYGroupsCountSumAverageVariance201012991 6826.3333333333135.333333333320111210049837.4166666667 121.53787878792012129431785.91666666672749.71969696972 013128029669.0833333333959.35606060612014125955496.252 940.0227272727ANOVASource of VariationSSdfMSFP-valueF
critBetween Groups984600.3333333334246150.083333333178.2154383340. 00002.5396886349Within Groups75965.6666666667551381.1939393939Total106056659w e conduct two regression analyses (i) what may have happened had the supplier initiative not been impelemented (ii) how the number of defects might further be reduced in the future.i) what might have happened had the supplier initiative not been implemented here the analysis is based on months from January 2010 to when the supplier initiative was done in august 2011. Let t be the number of months from December 2009; that is January 2010 be t=1, February 2010 be t=2 and so onDefects per million items received from suppliers is the dependent variabe while time is the independent variableDefectstime t8121810281338234832584868377831882798381082611819128 281383214847158391683217840188491985720The following is the regression equationSUMMARY OUTPUTRegression StatisticsMultiple R0.6994187048R Square0.4891865246Adjusted R Square0.4608079981Standard Error9.4427395385Observations20ANOVAdfSSMSFSignificanc e FRegression11537.02406015041537.024060150417.2379114202 0.0005989968Residual181604.975939849689.1653299916Total 193142CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept816.03684210534.3864495472186.03584364355. 14111788361825E- 31806.8212535732825.2524306373806.8212535732825.252430 6373X Variable 11.52030075190.36617373334.15185638240.00059899680.7509 9828492.28960321880.75099828492.2896032188Regression Equationy=1.520301x + 816.0368defects= 1.520301* t + 816.0368This means had the supplier initiative not taken place, the number of defects would have increased with timewhere t is the number of months from the baseline.had the supplier initiative of August 2011 not taken place, this regression
equation would have predicted what would have happened in subsequent months after august 2011ii)how the number of defects might further be reduced in the futurehere we analyze regression resuts from september 2011 when the supplier initiative was undertakenthe new baseline is august 2011, so for september 2011, t=1, october 2011 t=2, and so on. DefectsTime t8391842282838164824583668187825880498121080611798128 04137131470515686166821769518692196862067321681226962 36882467125645266172760328571295753054731542325323349 634472354603644137445384383943640The regression results are:SUMMARY OUTPUTRegression StatisticsMultiple R0.9750468977R Square0.9507164528Adjusted R Square0.9494195173Standard Error30.1520143865Observations40ANOVAdfSSMSFSignifican ce FRegression1666446.529080675666446.529080675733.0483948 9421.90959818846179E- 26Residual3834547.4709193246909.1439715612Total39700994 CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept897.73076923089.71653769392.39204309162.48 445466444305E- 46878.0606670317917.4008714299878.0606670317917.400871 4299X Variable 1-11.1819887430.4130025443- 27.07486647971.9095981884618E-26-12.0180686833- 10.3459088026-12.0180686833-10.3459088026The value of R- squared means the model is a good fit for the data.The p-values indicate statistical significanceRegression Equationy=-11.182X +897.7308defects=897.7308-11.182*there t is the number of months from august 2011 Defects After Delivery by Year 2010 2011 2012 2013 2014 9916 10049 9431 8029 5955 2010 2011 2012 2013 2014 812 828 824 682 571 2010 2011 2012 2013 2014 810 832 836 695 575 2010 2011 2012 2013 2014 813 847 818 692 547 2010 2011 2012 2013 2014 823 839 825 686 542 2010 2011 2012 2013 2014
832 832 804 673 532 2010 2011 2012 2013 2014 848 840 812 681 496 2010 2011 2012 2013 2014 837 849 806 696 472 2010 2011 2012 2013 2014 831 857 798 688 460 2010 2011 2012 2013 2014 827 839 804 671 441 2010 2011 2012 2013 2014 838 842 713 645 445 2010 2011 2012 2013 2014 826 828 705 617 438 2010 2011 2012 2013 2014 819 816 686 603 436 We can conclude that Defects had a slight increase from 2010 to 2011 which can be attributed to an increase in unit sales. But over the years from the years of 2010 to 2014 the amount of defects decreased overall . This shows that the company is evolving and improving their manufacturing process. Time to Pay SuppliersTime to Pay SuppliersMonthWorking DaysJan-108.32Feb-108.28Mar-108.29Apr-108.32May- 108.36Jun-108.35Jul-108.34Aug-108.32Sep-108.36Oct- 108.33Nov-108.32Dec-108.29Jan-117.89Feb-117.65Mar- 117.58Apr-117.53May-117.48Jun-117.45Jul-117.36Aug- 117.35Sep-117.32Oct-117.3Nov-117.27Dec-117.25Jan- 127.22Feb-127.21Mar-127.22Apr-127.29May-127.25Jun- 127.23Jul-127.28Aug-127.25Sep-127.24Oct-127.26Nov- 127.21Dec-127.23Jan-137.24Feb-137.19Mar-137.21Apr- 137.23May-137.22Jun-137.19Jul-137.17Aug-137.15Sep- 137.16Oct-137.16Nov-137.15Dec-137.14Jan-147.12Feb- 147.11Mar-147.11Apr-147.11May-147.11Jun-147.12Jul- 147.08Aug-147.09Sep-147.09Oct-147.04Nov-147.06Dec-147.08 Employee SatisfactionEmployee Satisfaction ResultsAverages using a 5 point scaleDesign &Sales & QuarterProductionSample sizeManagerSample sizeAdministrationSample sizeTotalSample size1st Q-112.861003.81103.51303.071402nd Q- 112.911003.76103.38303.071403rd Q- 112.841003.86103.45303.041404th Q- 112.831003.48103.61303.041401st Q-
122.911003.75203.37303.111502nd Q- 122.941003.92203.53303.191503rd Q- 122.861003.89203.47303.121504th Q- 122.831003.58203.66303.101501st Q- 132.951003.82203.71403.251602nd Q- 133.011004.01203.53403.271603rd Q- 133.031003.92203.62403.291604th Q- 132.961003.84203.48403.201601st Q- 143.051003.92203.52403.281602nd Q- 143.121004.00203.37403.291603rd Q- 143.061003.93203.46403.271604th Q- 143.021003.70203.59403.25160 EnginesEngine Production TimeSampleProduction Time (min)165.1time is the dependent variable and sample is the independent variable262.3360.4SUMMARY OUTPUT458.7558.1Regression Statistics656.9Multiple R0.9213573188757.0R Square0.8488993088856.5Adjusted R Square0.8457513778955.1Standard Error1.81826878671054.3Observations501153.71253.2ANOVA 1352.8dfSSMSFSignificance F1452.5Regression1891.5529337335891.5529337335269.66896 386722.48594348198823E- 211552.1Residual48158.69286626653.30610138061651.8Total4 91050.24581751.51851.3CoefficientsStandard Errort StatP- valueLower 95%Upper 95%Lower 95.0%Upper 95.0%1950.9Intercept58.18367346940.5220964329111.4423884 2141.29129366690705E- 5957.133928234659.233418704257.133928234659.2334187042 2050.5X Variable 1-0.29261464590.0178188871- 16.4216005272.48594348198821E-21-0.3284419196- 0.2567873721-0.3284419196-0.25678737212150.22250.0The value of R-squared means the model is a good fit for the data.2349.7The p-values indicate statistical significance2449.52549.3The regression equation is : y=58.18367-0.29261x2649.4Production Time=58.18367- 0.29261*x2749.1This means that as the number of units
produced increase, the production time reduces and therefore creating a more cost-effective means of production2849.02948.83048.53148.33248.23348.13447.93547. 73647.63747.43847.13946.94046.84146.74246.64346.54446.545 46.24646.34746.04845.84945.75045.6 Q4Anova: Single FactorSUMMARYGroupsCountSumAverageVarianceCurrent308 688289.62061.1448275862Process A308565285.54217.6379310345Process B308953298.4333333333435.3574712 644ANOVASource of VariationSSdfMSFP-valueF critBetween Groups2621.088888888921310.54444444440.58557509950.558 96481053.1012957567Within Groups194710.066666667872238.046743295Total197331.15555 555689 Transmission CostsUnit Tractor Transmission CostsQ4CurrentProcess AProcess B$242.00$242.00$292.00Anova: Single Factor$176.00$275.00$321.00$286.00$199.00$314.00SUMMA RY$269.00$219.00$242.00GroupsCountSumAverageVariance$3 27.00$273.00$278.00Current308688289.62061.1448275862$264 .00$265.00$300.00Process A308565285.54217.6379310345$296.00$435.00$301.00Process B308953298.4333333333435.3574712644$333.00$285.00$286.0 0$242.00$384.00$315.00$288.00$387.00$300.00ANOVA$314.0 0$299.00$304.00Source of VariationSSdfMSFP-valueF crit$302.00$145.00$300.00Between Groups2621.088888888921310.54444444440.58557509950.558 96481053.1012957567$335.00$266.00$351.00Within Groups194710.066666667872238.046743295$242.00$216.00$2 77.00$281.00$331.00$284.00Total197331.15555555689$289.00 $247.00$276.00$259.00$280.00$312.00$322.00$267.00$273.00 $209.00$210.00$281.00$282.00$391.00$303.00$304.00$297.00 $306.00$391.00$346.00$312.00$236.00$230.00$287.00$383.00 $332.00$306.00$299.00$301.00$312.00$300.00$277.00$295.00 $278.00$336.00$288.00$303.00$217.00$313.00$315.00$274.00
$286.00$321.00$339.00$338.00 Blade WeightBlade Weight SampleWeight14.88Question 4( Average blade weight)24.92we use the average function in Excel35.02average blade weight4.990844.9755.00for variability, we use the sample standard deviation64.99s.d.0.1092875674.8685.0795.04QUESTION 5 (probability blade weights will exceed 5.20)104.87we calculate the z-score associated with 5.20114.77z1.9142160368125.14probability (Z.Z>1.914216)0.027796135.04145.00154.88QUESTION 6 (probability blade weights will be less than 4.80)164.91175.09we calculate the z-score associated with 4.80184.97z-1.7458528672194.98probability (Z<- 1.74585)0.0404182609205.07215.03QUESTION 7 (actual pecentage less than 4.80 or greater than 5.20)225.12235.08less than 4.808244.86more than 5.207255.11total15264.92275.18actaul percentage <4.80 or > 5.204.2857%284.93295.12305.08QUESTION 8 (is the process stable over time)314.75we can make a scatter plot to investigate the stability of the process324.99335.00344.91355.18364.95374.63384.89395.1140 5.05415.03425.02434.96445.04454.93465.06475.07485.00495.0 3505.00514.95from the scatter plot, we can observe that the process is quite stable because most values are close to each other524.99535.02544.90Question 9 (are there any outliers)555.105.87565.01yes, there are possible outliers. For example,the 171st blade with a weight of 5.87 is an outlier because it is far from the other values.574.84585.01594.88QUESTION 10 (Is the distribution normal)604.97beloe mean180614.97above mean170625.06635.06since the number of values below the mean is close to the number of values above the mean, the distribution is pretty normal645.04654.87665.00675.03685.02695.02705.06715.2172 5.09734.97745.01754.90764.89774.93785.16795.02805.01815.1 0825.03835.07844.92855.08864.96874.74884.91895.12905.0091
4.93924.88934.88944.81955.16965.03974.87985.09994.941005. 081014.971025.231035.121045.091055.121064.931074.791085. 101095.121104.861115.001124.941134.951144.951154.871165. 091174.941185.011195.041205.051215.051224.971234.961244. 961254.991265.041274.911285.191295.031304.991315.121324. 971334.881345.071355.011364.891374.951385.091395.091404. 891414.931424.851435.031444.921455.091464.991474.921484. 871494.901505.021515.211525.021534.915451555.161565.0315 74.961585.041594.981605.071615.021625.081634.851644.9165 4.971665.091674.891684.871695.011704.971715.871725.33173 5.111745.071754.931764.991775.041785.141795.091805.06181 4.851824.931835.041845.091855.071864.991875.011884.88189 4.931905.11914.941924.881934.891944.891954.851964.821975. 021984.91994.732005.042015.072024.812035.042045.032055.0 12065.142075.122084.892094.912104.972114.982125.012135.0 12145.092154.932165.042175.112185.072194.952204.862215.1 32224.952235.222244.812254.912264.952274.942284.812295.1 12304.812314.972325.072335.032344.812354.952364.892375.0 82384.932394.992404.942415.132425.022435.072444.822455.0 32464.852474.892484.822495.182505.022515.052524.882535.0 82544.982555.022564.992575.022585.032595.022605.072614.9 52624.952634.942645.122655.082664.912674.962684.962694.9 42705.192714.912725.012734.932745.052754.962764.922774.9 52785.082794.972805.042814.942824.982835.032845.052854.9 12865.092875.212884.872895.022904.812914.962925.062934.8 62944.962954.992964.942975.062984.952995.023005.013015.0 43025.013035.023045.033055.183065.083075.143084.923094.9 73104.923115.143124.923135.033144.983154.763164.943174.9 23184.913194.963205.023215.133225.133234.923244.983254.8 93264.883275.113285.113295.083305.033314.943324.883334.9 13344.863354.893364.913374.873384.933395.143404.873414.9 83424.883434.883445.013454.933464.933474.993484.913494.9 63504.78 Blade Weights Weight 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 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 4.88 4.92 5.0199999999999996 4.97 5 4.99 4.8600000000000003 5.07 5.04 4.87 4.7699999999999996 5.14 5.04 5 4.88 4.91 5.09 4.97 4.9800000000000004 5.07 5.03 5.12 5.08 4.8600000000000003 5.1100000000000003 4.92 5.18 4.93 5.12 5.08 4.75 4.99 5 4.91 5.18 4.95 4.63 4.8899999999999997 5.1100000000000003 5.05
5.03 5.0199999999999996 4.96 5.04 4.93 5.0599999999999996 5.07 5 5.03 5 4.95 4.99 5.0199999999999996 4.9000000000000004 5.0999999999999996 5.01 4.84 5.01 4.88 4.97 4.97 5.0599999999999996 5.0599999999999996 5.04 4.87 5 5.03 5.0199999999999996 5.0199999999999996 5.0599999999999996 5.21 5.09 4.97 5.01 4.9000000000000004 4.8899999999999997 4.93 5.16 5.0199999999999996 5.01 5.0999999999999996 5.03 5.07 4.92 5.08 4.96 4.74 4.91 5.12 5 4.93 4.88 4.88 4.8099999999999996 5.16 5.03 4.87 5.09 4.9400000000000004 5.08 4.97 5.23 5.12 5.09 5.12 4.93 4.79 5.0999999999999996 5.12 4.8600000000000003 5 4.9400000000000004 4.95 4.95 4.87 5.09 4.9400000000000004 5.01 5.04 5.05 5.05 4.97 4.96 4.96 4.99 5.04 4.91 5.19 5.03 4.99 5.12 4.97 4.88 5.07 5.01 4.8899999999999997 4.95 5.09 5.09 4.8899999999999997 4.93 4.8499999999999996 5.03 4.92 5.09 4.99 4.92 4.87 4.9000000000000004 5.0199999999999996 5.21 5.0199999999999996 4.9000000000000004 5 5.16 5.03 4.96 5.04 4.9800000000000004 5.07 5.0199999999999996 5.08 4.8499999999999996 4.9000000000000004 4.97 5.09 4.8899999999999997 4.87 5.01 4.97 5.87 5.33 5.1100000000000003 5.07 4.93 4.99 5.04 5.14 5.09 5.0599999999999996 4.8499999999999996 4.93 5.04 5.09 5.07 4.99 5.01 4.88 4.93 5.0999999999999996 4.9400000000000004 4.88 4.8899999999999997 4.8899999999999997 4.8499999999999996 4.82 5.0199999999999996 4.9000000000000004 4.7300000000000004 5.04 5.07 4.8099999999999996 5.04 5.03 5.01 5.14 5.12 4.8899999999999997 4.91 4.97 4.9800000000000004 5.01 5.01 5.09 4.93 5.04 5.1100000000000003 5.07 4.95 4.8600000000000003 5.13 4.95 5.22 4.8099999999999996 4.91 4.95 4.9400000000000004
4.8099999999999996 5.1100000000000003 4.8099999999999996 4.97 5.07 5.03 4.8099999999999996 4.95 4.8899999999999997 5.08 4.93 4.99 4.9400000000000004 5.13 5.0199999999999996 5.07 4.82 5.03 4.8499999999999996 4.8899999999999997 4.82 5.18 5.0199999999999996 5.05 4.88 5.08 4.9800000000000004 5.0199999999999996 4.99 5.0199999999999996 5.03 5.0199999999999996 5.07 4.95 4.95 4.9400000000000004 5.12 5.08 4.91 4.96 4.96 4.9400000000000004 5.19 4. 91 5.01 4.93 5.05 4.96 4.92 4.95 5.08 4.97 5.04 4.9400000000000004 4.9800000000000004 5.03 5.05 4.91 5.09 5.21 4.87 5.0199999999999996 4.8099999999999996 4.96 5.0599999999999996 4.8600000000000003 4.96 4.99 4.9400000000000004 5.0599999999999996 4.95 5.0199999999999996 5.01 5.04 5.01 5.0199999999999996 5.03 5.18 5.08 5.14 4.92 4.97 4.92 5.14 4.92 5.03 4.9800000000000004 4.76 4.9400000000000004 4.92 4.91 4.96 5.0199999999999996 5.13 5.13 4.92 4.9800000000000004 4.8899999999999997 4.88 5.1100000000000003 5.1100000000000003 5.08 5.03 4.9400000000000004 4.88 4.91 4.8600000000000003 4.8899999999999997 4.91 4.87 4.93 5.14 4.87 4.9800000000000004 4.88 4.88 5.01 4.93 4.93 4.99 4.91 4.96 4.78 sample weight Mower TestMower Test Functional PerformanceSampleObservation12345678910111213141516171 81920212223242526272829301PassFailPassPassPassPassPassPa ssPassPassPassPassPassPassPassPassPassPassPassPassPassPass
PassPassPassPassPassPassPassPass2PassFailPassPassPassPassP assPassPassPassPassPassPassPassPassPassPassPassPassPassFail PassPassPassPassPassPassPassPassPass3PassPassPassPassPassP assPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassFailPassPassPassPassPassPass4PassPassPassPassP assPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPass5PassPassPassP assPassPassPassPassPassPassPassPassFailPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPass6PassPassP assPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPassPass7PassP assPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPassPassPass8P assPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassFailPassPassPassPassPassPas s9PassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPassPassPassPa ssPass10PassPassPassPassPassFailPassPassPassPassPassPassPas sPassPassPassPassPassPassPassPassPassPassPassPassPassPassP assPassPass11PassPassPassPassPassPassPassPassPassPassPassP assPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPass12PassFailPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPassPassPassPa ssPassPassPassPassPass13PassPassPassPassPassPassPassPassPa ssPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassFail14PassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPassPassPassPa ssPassPassPassPassPassPassPassPass15PassPassPassPassPassPa ssPassPassPassPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPass16PassPassPassPass PassFailPassPassPassPassPassPassPassPassPassPassPassPassPas sPassPassPassPassPassPassPassPassPassPassPass17PassPassPas sPassPassPassPassPassPassPassPassPassPassPassPassPassPassP assPassPassPassPassPassPassPassPassPassPassPassPass18PassP assPassPassFailPassPassPassPassPassPassPassPassPassPassPass PassPassPassPassPassPassPassPassPassPassPassPassPassPa ss19
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample
Dealer SatisfactionDealer Satisfaction Survey Scale012345Sample

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