Use Excel to develop a regression model for the Consumer Food Database (using the “Excel Databases.xls” file on Blackboard) to predict Annual Food Spending by Annual Household Income. Suppose a...


Use Excel to develop a regression model for the Consumer Food Database (using the “Excel Databases.xls” file on Blackboard) to predict Annual Food Spending by Annual Household Income.


Suppose a households annual income is $60,000.  Predict how much they spend on food per year.  Write your answer as a number (do not include the $ sign or comma) and round to 1 decimal place.





































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































Annual Food Spending ($)Annual Household Income           ($)Non mortgage household debt ($)Region:   1 = NE     2 = MW    3 = S       4 = WLocation:   1 = Metro      2 = Outside Metro
8909566972318011
568435945705211
10706526871614911
14112740412183911
13855631821886611
15619790642189911
269425981877411
9127574241576611
13514720452768511
631438046854511
7622524082805711
432241405699811
380529684480611
6674492461359211
734741491408811
2911267031587611
8026487531671411
8567555551678311
10345714832140711
8694509801911411
882146403781711
8678519271441511
14331847691729511
9619590621668711
9286579521416111
8206583551953811
16408816941518711
12757695221465111
1774096132011
7739577962205711
1538388276189611
457932264797911
1167965928011
12877699242733011
1623291108987611
9621540701990811
8171472381781911
12128774273134011
864259805496311
1240060334663211
9185541141859312
7862406801520212
977558263148612
6771520082171312
3059396431217912
13211703091322112
740846450560212
11581761403387412
14233808331147812
335231899276212
263021647266312
9093659241135512
1265265923513212
9559628111261312
611242335314912
10431651341519612
12630646212143312
457836553550212
9551629101137612
10262707271328712
9551576341185721
10143565491613621
8955596621162721
10197573501843221
11234564471087121
932061136021
908951526490221
12300799791727021
11484667331514521
11215753591561121
720440795897521
557939128657621
11723754821250821
935363998021
776145845667121
426138223857621
983066787117821
123867785293621
8673558251416721
1094457022901821
9910642631276821
9928758811742321
4264343432132321
7971412432100921
8290530212015121
1266966991925021
7272497192083821
9784583991606521
918750477940721
5866391122040921
9456518861166822
62703479714622
951862348520122
10968787041700222
8865536203200422
9226515771592222
4913347611770422
6976609681779922
815251281816722
2887250131876322
8062592381081522
8895473441181422
8444526452246922
6148353091713922
4563343551061222
8185506302118731
3391290561573531
7436487211836331
9522504591647831
11290728052123831
10403569542221831
4693393432469631
5626388331437131
11869550213557631
130557760581731
8783579371859131
13031633432553131
3681364791795031
5549403811425731
4108263092658131
6314414212247031
7700545792906531
7479405513175731
909350369640431
9863544222433431
8043518362621332
9552736003637432
9286518732963132
7987480031726132
3875365191357932
10746751521065932
6888449742371132
547948923459432
6949437692122132
10650759473335732
5188414233364132
5311401891779132
469136772582932
8056596901959432
11304536542306632
81125906724032
869665962032
5869372541015732
3776335681414332
1182956934032
13087888221756541
10986596352786341
5762384071886741
11617786271189441
9895477102293041
16293644433168741
8185588713542441
13972879541154941
11243547781255241
4635398251949441
10063495361219541
8426601021378741
7436491392235641
1174751052455341
15397705001202541
6842548941621741
967860570410641
12852576253122841
10114569562590741
849661400109341
6689505321710641
15696727741779341
9841699812160741
12529668911768941
10210674311999541
8868647821448941
6426389871786441
1109664867583941
1008650421868941
2587270761753441
12492517842028442
8456541352203742
6801532912334242
6339498043494342
7802522052857942
9717728412234942
6026462382016542
5618459381053842
10217777161851642
833859711798042
9048421061978642
401736462993542
10906534031817742
1514871290669642
8830667592097242
8481576162876742
1135876221137342
1055378202592042
6969551642479542
13219611712148242
3543340932596942
7326506471075042
8458598982294042
11766528842597042
990873629711242
Jun 06, 2022
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