青年女装预测案例VIP专享VIP免费

某青年女装十三年中每个季度的销售额及其相关影响因素的数据如表 3-1所示，取前十二年的数据建立数学模型，其中购买力是指人均购买的能力，单位：元；文化程度中 1 代表初中文凭，2 代表高中文凭，3 代表大学以上文凭；生产状况中 0 代表稳步生产，1 代表加班。用多元线性回归法进行预测，求出其数学模型，并进行误差及精度检验。表 3-1 销售数据和影响因素的数据时间（t）季度(X1)男女比例(X3)购买力(X2)人均购买数(X4)文化程度(X5)生产状况(X6)人口数(X7)销售额Y12345678910111213141516171819202122231993 12341994 12341995 12341996 12341997 12341998 123121211121110991091812111111108810101516163503073183043024294544404553901333503513833603833403024004551131981998888888888488888888846611111111112111111111311000000000010000000001111651301501501401982202152251901151651531751751701601401502259595973017.603043.542094.352809.843274.803163.282114.313024.573327.483493.482439.933490.793685.083661.232378.433459.553849.633701.182642.383585.524078.663907.062828.46242526272829303132333435363738394041424344454647484950515241999 12342000 12342001 12342002 12342003 12342004 12342005 1234161521181518131514151491516141920131616161612121498111220097971101071041211993603073189497140113989723222525025023235040035126236029038064444446888.4444466666888848413222221111.3131211111111121111111111000.111111111100001018588468790951139021520021093889095.48100105100881001651751531451632431904089.504339.614148.602916.454084.644242.423997.582881.014036.234360.334360.533172.184223.764690.484694.483342.354577.634965.465026.053470.244525.945258.715189.583596.763881.605349.375261.713655.125043.65其数学模型为：Y=2332.94405+161.348691×X1-0.0531439×X2 （3-15）表 3-3 预测值及其它参数年份销售额 Y预测值 ^YY−¯YY− ^Y^Y−¯YX 1− ¯X1X 2−¯X21993 12341994 12341995 12341996 12341997 12341998 12341999 123017.63043.542094.352809.843274.83163.282114.313024.573327.483493.482439.933490.793685.083661.232378.433459.553849.633701.182642.383585.524078.663907.062828.464089.54339.614148.62798.392800.6752800.092800...