Tabelas para consultaTabela da distribuição t-studentGrau de liberdadeÁrea da cauda superior0,10,050,0250,010,00513,0786,31412,70631,82163,65721,8862,924,3036,9659,92531,6382,3533,1824,5415,84141,5332,1322,7763,7474,60451,4762,0152,5713,3654,03261,441,9432,4473,1433,70771,4151,8952,3652,9983,49981,3971,862,3062,8963,35591,3831,8332,2622,8213,25101,3721,8122,2282,7643,169111,3631,7962,2012,7183,106121,3561,7822,1792,6813,055131,351,7712,162,653,012141,3451,7612,1452,6242,977151,3411,7532,1312,6022,947161,3371,7462,122,5832,921171,3331,742,112,5672,898181,331,7342,1012,5522,878191,3281,7292,0932,5392,861201,3251,7252,0862,5282,845211,3231,7212,082,5182,831221,3211,7172,0742,5082,819231,3191,7142,0692,52,807241,3181,7112,0642,4922,797251,3161,7082,062,4852,787261,3151,7062,0562,4792,779271,3141,7032,0522,4732,771281,3131,7012,0482,4672,763291,3111,6992,0452,4622,756301,311,6972,0422,4572,75401,3031,6842,0212,4232,7041201,2891,6581,982,3582,6172001,2861,6531,9722,3452,601Tabela da distribuição Qui-quadrado Probabilidade (Xn2≥x)Grau de liberdadeÁrea na cauda superior0,250,10,050,0250,010,0050,00250,0010,000511,322,713,845,026,637,889,1410,8312,1222,774,615,997,389,2110,611,9813,8215,234,116,257,819,3511,3412,8414,3216,2717,7345,397,789,4911,1413,2814,8616,4218,472056,639,2411,0712,8315,0916,7518,3920,5222,1167,8410,6412,5914,4516,8118,5520,2522,4624,179,0412,0214,0716,0118,4820,2822,0424,3226,02810,2213,3615,5117,5320,0921,9523,7726,1227,87911,3914,6816,9219,0221,6723,5925,4627,8829,671012,5515,9918,3120,4823,2125,1927,1129,5931,421113,717,2819,6821,9224,7226,7628,7331,2633,141214,8518,5521,0323,3426,2228,330,3232,9134,821315,9819,8122,3624,7427,6929,8231,8834,5336,481417,1221,0623,6826,1229,1431,3233,4336,1238,111518,2522,312527,4930,5832,834,9537,739,721619,3723,5426,328,853234,2736,4639,2541,311720,4924,7727,5930,1933,4135,7237,9540,7942,881821,625,9928,8731,5334,8137,1639,4242,3144,431922,7227,230,1432,8536,1938,5840,8843,8245,972023,8328,4131,4134,1737,574042,3445,3147,52124,9329,6232,6735,4838,9341,443,7846,849,012226,0430,8133,9236,7840,2942,845,248,2750,512327,1432,0135,1738,0841,6444,1846,6249,73522428,2433,236,4239,3642,9845,5648,0351,1853,482529,3434,3837,6540,6544,3146,9349,4452,6254,952630,4335,5638,8941,9245,6448,2950,8354,0556,412731,5336,7440,1143,1946,9649,6452,2255,4857,862832,6237,9241,3444,4648,2850,9953,5956,8959,32933,7139,0942,5645,7249,5952,3454,9758,360,733034,840,2643,7746,9850,8953,6756,3359,762,163540,2246,0649,853,257,3460,2763,0866,6269,24045,6251,8155,7659,3463,6966,7769,773,476,094550,9857,5161,6665,4169,9673,1776,2280,0882,885056,3363,1767,571,4276,1579,4982,6686,6689,56100109,14118,5124,34129,56135,81140,17144,29149,45153,17Tabela da distribuição Normal padrãoProbabilidade da distribuição normal padrão acumulada na cauda superior - Prob(Z>Z0)Z0Segunda decimal de Z0.00,010,020,030,040,050,060,070,080,090,000,50,4960,4920,4880,4840,48010,47610,47210,46810,46410,100,46020,45620,45220,44830,44430,44040,43640,43250,42860,42470,200,42070,41680,41290,4090,40520,40130,39740,39360,38970,38590,300,38210,37830,37450,37070,36690,36320,35940,35570,3520,34830,400,34460,34090,33720,33360,330,32640,32280,31920,31560,31210,500,30850,3050,30150,29810,29460,29120,28770,28430,2810,27760,600,27430,27090,26760,26430,26110,25780,25460,25140,24830,24510,700,2420,23890,23580,23270,22960,22660,22360,22060,21770,21480,800,21190,2090,20610,20330,20050,19770,19490,19220,18940,18670,900,18410,18140,17880,17620,17360,17110,16850,1660,16350,16111,000,15870,15620,15390,15150,14920,14690,14460,14230,14010,13791,100,13570,13350,13140,12920,12710,12510,1230,1210,1190,1171,200,11510,11310,11120,10930,10750,10560,10380,1020,10030,09851,300,09680,09510,09340,09180,09010,08850,08690,08530,08380,08231,400,08080,07930,07780,07640,07490,07350,07210,07080,06940,06811,500,06680,06550,06430,0630,06180,06060,05940,05820,05710,05591,600,05480,05370,05260,05160,05050,04950,04850,04750,04650,04551,700,04460,04360,04270,04180,04090,04010,03920,03840,03750,03671,800,03590,03510,03440,03360,03290,03220,03140,03070,03010,02941,900,02870,02810,02740,02680,02620,02560,0250,02440,02390,02332,000,02280,02220,02170,02120,02070,02020,01970,01920,01880,01832,100,01790,01740,0170,01660,01620,01580,01540,0150,01460,01432,200,01390,01360,01320,01290,01250,01220,01190,01160,01130,0112,300,01070,01040,01020,00990,00960,00940,00910,00890,00870,00842,400,00820,0080,00780,00750,00730,00710,00690,00680,00660,00642,500,00620,0060,00590,00570,00550,00540,00520,00510,00490,00482,600,00470,00450,00440,00430,00410,0040,00390,00380,00370,00362,700,00350,00340,00330,00320,00310,0030,00290,00280,00270,00262,800,00260,00250,00240,00230,00230,00220,00210,00210,0020,00192,900,00190,00180,00180,00170,00160,00160,00150,00150,00140,00143,000,00130,00130,00130,00120,00120,00110,00110,00110,0010,0013,100,0010,00090,00090,00090,00080,00080,00080,00080,00070,00073,200,00070,00070,00060,00060,00060,00060,00060,00050,00050,00053,300,00050,00050,00050,00040,00040,00040,00040,00040,00040,00033,400,00030,00030,00030,00030,00030,00030,00030,00030,00030,00023,500,00020,00020,00020,00020,00020,00020,00020,00020,00020,00023,600,00020,00020,00010,00010,00010,00010,00010,00010,00010,00013,700,00010,00010,00010,00010,00010,00010,00010,00010,00010,00013,800,00010,00010,00010,00010,00010,00010,00010,00010,00010,00013,900,00000,00000,00000,00000,00000,00000,00000,00000,00000,00004,000,00000,00000,00000,00000,00000,00000,00000,00000,00000,0000 O gráfico a seguir representa uma série temporal.Com a finalidade de identificar o modelo, devem ser observadas a função de autocorrelação (FAC) e a função de autocorrelação parcial (FACP) da série com uma diferença que está ilustrada nos gráficos a seguir.Seja a notação de modelo tipo ARIMA (p, d, q), sendo p, a ordem da parte autorregressiva; d, o grau da diferenciação; e q, a ordem da parte de médias móveis.O modelo que melhor representa a série temporal é:

O gráfico a seguir representa uma série temporal.Com a fi...

Q2422154

Ano: 2022

Prova: FGV - TJDFT - Analista Judiciário - Área Estatística - 2022

O gráfico a seguir representa uma série temporal.

Com a finalidade de identificar o modelo, devem ser observadas a função de autocorrelação (FAC) e a função de autocorrelação parcial (FACP) da série com uma diferença que está ilustrada nos gráficos a seguir.

Seja a notação de modelo tipo ARIMA (p, d, q), sendo p, a ordem da parte autorregressiva; d, o grau da diferenciação; e q, a ordem da parte de médias móveis.

O modelo que melhor representa a série temporal é:

ARIMA(0,0,1);

ARIMA(0,1,1);

ARIMA(1,0,1);

ARIMA(1,1,0);

ARIMA(1,1,1).

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O gráfico a seguir representa uma série temporal.Com a finalidade de identificar o mode...