LCE_1270_Gestão Certificação e Estatística

sexta-feira, 6 de dezembro de 2024

Prova 1 ponto 136

Prova valendo 1 ponto, tentem aproveitar para testar o nível de vocês, a prova vale muito pouco, simulamos a resolução de um problema da vida profissional

- Manterei os horários de consulta no verão, podem ser utilizados para melhorar o nível, notas e frequências

Regressão Múltipla em Excel ou LOffice Calc e SAS (proc reg e robustreg)

Resolver com e sem o outlier e discutir os resultados.

Outlier último registro.

DBO	ICobV	ICArb	Bcont	Dis_Pl	IBD_A
1,604	89	60	11	9	90
0,385	90	61	10	8,9	91
0,216	91	62	9	9,1	92
0,303	90	59	10	8,8	89
1,961	20	12	81	0,2	20
0,782	21	14	79	0,3	22
0,57	22	15	78	0,25	23
2,187	22	12	77	0,2	24
0,764	59	35	41	6	60
0,273	60	32	40	6,5	61
1,883	64	33	38	5,8	63
0,581	62	32	37	5,6	62
0,18	79	50	21	8,2	80
0,007	80	49	20	7,8	79
2,028	80	48	18	8,2	81
2,431	79	47	21	7,7	78

0,216

9,1

quinta-feira, 5 de dezembro de 2024

Gabriel WhatsApp: +55 19 988 627 438 e E-Mail

WhatsApp: +55 19 988 627 438

E-Mail: gasarrie@usp.br

Prova valendo 1 ponto

Prova valendo 1 ponto, tentem aproveitar para testar o nível de vocês, a prova vale muito pouco, simulamos a resolução de um problema da vida profissional

- Manterei os horários de consulta no verão, podem ser utilizados para melhorar o nível, notas e frequências

Regressão Múltipla em Excel ou LOffice Calc e SAS (proc reg e robustreg)

Resolver com e sem o outlier e discutir os resultados.

Bu_Unit	Sales	Price	Qu_level	Claims	NPS	PV	Satisfac
1	65,98108	97,8022	96,77419	13,58025	98,9011	19	97,82459
2	15,8371	98,9011	98,3871	12,34568	97,8022	29	98,91459
3	8,885232	100	100	11,11111	100	21	100
4	12,46401	98,9011	95,16129	12,34568	96,7033	94	9?,??913
5	80,66639	21,97802	19,35484	100	2,197802	34	21,73913
6	32,16783	23,07692	22,58065	97,53086	3,296703	64	23,91304
7	23,44714	24,17582	24,19355	96,2963	2,747253	61	25
8	89,96298	24,17582	19,35484	95,06173	2,197802	25	26,08696
9	31,4274	64,83516	56,45161	50,61728	65,93407	10	65,21739
10	11,22995	65,93407	51,6129	49,38272	71,42857	3	66,30435
11	77,45784	70,32967	53,22581	46,91358	63,73626	56	68,47826
12	23,89963	68,13187	51,6129	45,67901	61,53846	4	67,3913
13	7,40436	86,81319	80,64516	25,92593	90,10989	90	86,95652
14	0,287947	87,91209	79,03226	24,69136	85,71429	48	85,86957
15	83,42246	87,91209	77,41935	22,22222	90,10989	78	88,04348
16	100	86,81319	75,80645	25,92593	84,61538	88	84,78261



Outlier

17	8,885232	100	100	11,11111	100	21	20

domingo, 24 de novembro de 2024

Arquivo do Weka para MLS para Clasificação

Arquivo para Download:

Arquivo Franco Swizo

quinta-feira, 21 de novembro de 2024

ANOVA para selecionar Variáveis Preditoras a serem utilizadas em Cluster Analysis, PCA e ML Supervisionado para Classificação (Rede Neural, Random Forest, Support Vector Machine etc.)

ANOVA para selecionar Variáveis Preditoras a serem utilizadas em Cluster Analysis, PCA e ML Supervisionado para Classificação (Rede Neural, Random Forest, Support Vector Machine etc.)

Qualidade de Vida - Cluster Analysis (ML Não Supervisionado para Agrupamentos Multivariados)

data QV;

input Categ $ IMC Movim KCal;

cards;

ATL 20.9 60.9 3259

ATL 21.3 54.8 3100

ATL 19.3 49.6 2800

ATL 21.1 52.3 3300

SEMI 22.4 14.9 2600

SEMI 21.9 17.8 2700

SEMI 23.8 18.6 3200

SEMI 24.1 15.1 3300

SEDE 27.3 2.5 2700

SEDE 23.4 4.3 2300

SEDE 25.2 2.3 2600

SEDE 26.4 2.6 3200

PROF 26.2 4.1 2600

PROF 24.2 2.1 2700

PROF 25.4 1.9 2650

;

proc print;

run;

/* input Categ $ IMC Movim KCal;*/

proc anova;

class Categ;

model IMC Movim KCal = Categ;

means Categ / tukey lines;

run;

Cálculo de Medias por Pivot Table

Categ	IMC	Movim	Kcal
ATL	20,9	60,9	3259
ATL	21,3	54,8	3100
ATL	19,3	49,6	2800
ATL	21,1	52,3	3300
SEMI	22,4	14,9	2600
SEMI	21,9	17,8	2700
SEMI	23,8	18,6	3200
SEMI	24,1	15,1	3300
SEDE	27,3	2,5	2700
SEDE	23,4	4,3	2300
SEDE	25,2	2,3	2600
SEDE	26,4	2,6	3200
PROF	26,2	4,1	2600
PROF	24,2	2,1	2700
PROF	25,4	1,9	2650

Cluster com Variáveis Preditoras Significativas Comparar com Todas

Primeiro com Todas as Variáveis Preditoras

data pessoas;

input cat $ imc corr kcal;

cards;

ATL 20.65 54.4 3114.75

PROF 25.26666667 2.7 2650

SEDE 25.575 2.925 2700

SEMI 23.05 16.6 2950

;

proc cluster data=pessoas outtree = arvore method = average;

var imc corr kcal;

id cat;

run;

PROC TREE DATA = arvore;

RUN;

Agora Fazer somente com as Variáveis Preditoras Significativas

Somente muda este comando

var imc corr;

Dinheiro Falso - Rede Neural (ML S para Clasif.)

Programa SAS

data apolinario;

input obs Status length Left Rigth Bottom Top Diagonal Transpar;

cards;

1 0 214.8 131 131.1 9 9.7 141.459 8.342459

2 0 214.6 129.7 129.7 8.1 9.5 141.7 9.005343

3 0 214.8 129.7 129.7 8.7 9.6 142.2 4.293085

4 0 214.8 129.7 129.6 7.5 10.4 142 5.281225

5 0 215 129.6 129.7 10.4 7.7 141.8 1.513307

6 0 215.7 130.8 130.5 9 10.1 141.4 5.739582

7 0 215.5 129.5 129.7 7.9 9.6 141.6 3.58029

8 0 214.5 129.6 129.2 7.2 10.7 141.7 8.620212

9 0 214.9 129.4 129.7 8.2 11 141.9 6.128928

10 0 215.2 130.4 130.3 9.2 10 140.7 1.225479

11 0 215.3 130.4 130.3 7.9 11.7 141.8 0.442973

12 0 215.1 129.5 129.6 7.7 10.5 142.2 9.165131

13 0 215.2 130.8 129.6 7.9 10.8 141.4 3.034573

14 0 214.7 129.7 129.7 7.7 10.9 141.7 4.929624

15 0 215.1 129.9 129.7 7.7 10.8 141.8 3.996129

16 0 214.5 129.8 129.8 9.3 8.5 141.6 5.107183

17 0 214.6 129.9 130.1 8.2 9.8 141.7 3.666467

18 0 215 129.9 129.7 9 9 141.9 4.605725

19 0 215.2 129.6 129.6 7.4 11.5 141.5 6.26076

20 0 214.7 130.2 129.9 8.6 10 141.9 6.538608

21 0 215 129.9 129.3 8.4 10 141.4 0.450759

22 0 215.6 130.5 130 8.1 10.3 141.6 3.106727

23 0 215.3 130.6 130 8.4 10.8 141.5 2.091035

24 0 215.7 130.2 130 8.7 10 141.6 0.093906

25 0 215.1 129.7 129.9 7.4 10.8 141.1 7.069552

26 0 215.3 130.4 130.4 8 11 142.3 6.143458

27 0 215.5 130.2 130.1 8.9 9.8 142.4 2.899919

28 0 215.1 130.3 130.3 9.8 9.5 141.9 3.056647

29 0 215.1 130 130 7.4 10.5 141.8 7.640232

30 0 214.8 129.7 129.3 8.3 9 142 0.911595

31 0 215.2 130.1 129.8 7.9 10.7 141.8 9.286659

32 0 214.8 129.7 129.7 8.6 9.1 142.3 1.654785

33 0 215 130 129.6 7.7 10.5 140.7 9.087692

34 0 215.6 130.4 130.1 8.4 10.3 141 3.066002

35 0 215.9 130.4 130 8.9 10.6 141.4 9.669812

36 0 214.6 130.2 130.2 9.4 9.7 141.8 7.152279

37 0 215.5 130.3 130 8.4 9.7 141.8 5.814042

38 0 215.3 129.9 129.4 7.9 10 142 8.451992

39 0 215.3 130.3 130.1 8.5 9.3 142.1 8.270316

40 0 213.9 130.3 129 8.1 9.7 141.3 2.374091

41 0 214.4 129.8 129.2 8.9 9.4 142.3 7.882688

42 0 214.8 130.1 129.6 8.8 9.9 140.9 8.628963

43 0 214.9 129.6 129.4 9.3 9 141.7 6.522981

44 0 214.9 130.4 129.7 9 9.8 140.9 6.203108

45 0 214.8 129.4 129.1 8.2 10.2 141 6.605354

46 0 214.3 129.5 129.4 8.3 10.2 141.8 4.43922

47 0 214.8 129.9 129.7 8.3 10.2 141.5 1.899184

48 0 214.8 129.9 129.7 7.3 10.9 142 8.704295

49 0 214.6 129.7 129.8 7.9 10.3 141.1 2.990982

50 0 214.5 129 129.6 7.8 9.8 142 0.571166

51 0 214.6 129.8 129.4 7.2 10 141.3 6.407039

52 0 215.3 130.6 130 9.5 9.7 141.1 0.235993

53 0 214.5 130.1 130 7.8 10.9 140.9 3.450459

54 0 215.4 130.2 130.2 7.6 10.9 141.6 1.381513

55 0 214.5 129.4 129.5 7.9 10 141.4 1.621623

56 0 215.2 129.7 129.4 9.2 9.4 142 7.640185

57 0 215.7 130 129.4 9.2 10.4 141.2 1.496712

58 0 215 129.6 129.4 8.8 9 141.1 5.754074

59 0 215.1 130.1 129.9 7.9 11 141.3 0.169488

60 0 215.1 130 129.8 8.2 10.3 141.4 4.48128

61 0 215.1 129.6 129.3 8.3 9.9 141.6 0.338244

62 0 215.3 129.7 129.4 7.5 10.5 141.5 6.148626

63 0 215.4 129.8 129.4 8 10.6 141.5 3.799348

64 0 214.5 130 129.5 8 10.8 141.4 6.141745

65 0 215 130 129.8 8.6 10.6 141.5 5.479944

66 0 215.2 130.6 130 8.8 10.6 140.8 3.914293

67 0 214.6 129.5 129.2 7.7 10.3 141.3 0.979716

68 0 214.8 129.7 129.3 9.1 9.5 141.5 0.416134

69 0 215.1 129.6 129.8 8.6 9.8 141.8 4.493104

70 0 214.9 130.2 130.2 8 11.2 139.6 8.433149

71 0 213.8 129.8 129.5 8.4 11.1 140.9 3.194225

72 0 215.2 129.9 129.5 8.2 10.3 141.4 7.989399

73 0 215 129.6 130.2 8.7 10 141.2 9.189951

74 0 214.4 129.9 129.6 7.5 10.5 141.8 8.151371

75 0 215.2 129.9 129.7 7.2 10.6 142.1 1.175441

76 0 214.1 129.6 129.3 7.6 10.7 141.7 9.425796

77 0 214.9 129.9 130.1 8.8 10 141.2 0.608648

78 0 214.6 129.8 129.4 7.4 10.6 141 8.879565

79 0 215.2 130.5 129.8 7.9 10.9 140.9 3.996958

80 0 214.6 129.9 129.4 7.9 10 141.8 2.213717

81 0 215.1 129.7 129.7 8.6 10.3 140.6 8.99883

82 0 214.9 129.8 129.6 7.5 10.3 141 7.949556

83 0 215.2 129.7 129.1 9 9.7 141.9 4.350476

84 0 215.2 130.1 129.9 7.9 10.8 141.3 6.683159

85 0 215.4 130.7 130.2 9 11.1 141.2 5.799778

86 0 215.1 129.9 129.6 8.9 10.2 141.5 4.722314

87 0 215.2 129.9 129.7 8.7 9.5 141.6 8.674677

88 0 215 129.6 129.2 8.4 10.2 142.1 9.273823

89 0 214.9 130.3 129.9 7.4 11.2 141.5 5.012061

90 0 215 129.9 129.7 8 10.5 142 5.42594

91 0 214.7 129.7 129.3 8.6 9.6 141.6 8.5421

92 0 215.4 130 129.9 8.5 9.7 141.4 4.943298

93 0 214.9 129.4 129.5 8.2 9.9 141.5 8.712418

94 0 214.5 129.5 129.3 7.4 10.7 141.5 4.579332

95 0 214.7 129.6 129.5 8.3 10 142 7.852574

96 0 215.6 129.9 129.9 9 9.5 141.7 7.481017

97 0 215 130.4 130.3 9.1 10.2 141.1 1.91562

98 0 214.4 129.7 129.5 8 10.3 141.2 1.603

99 0 215.1 130 129.8 9.1 10.2 141.5 4.368422

100 0 214.7 130 129.4 7.8 10 141.2 9.289701

101 1 214.4 130.1 130.3 9.7 11.7 139.8 2.529576

102 1 214.9 130.5 130.2 11 11.5 139.5 5.231355

103 1 214.9 130.3 130.1 8.7 11.7 140.2 1.099865

104 1 215 130.4 130.6 9.9 10.9 140.3 9.704009

105 1 214.7 130.2 130.3 11.8 10.9 139.7 2.097141

106 1 215 130.2 130.2 10.6 10.7 139.9 4.749958

107 1 215.3 130.3 130.1 9.3 12.1 140.2 6.332

108 1 214.8 130.1 130.4 9.8 11.5 139.9 8.013084

109 1 215 130.2 129.9 10 11.9 139.4 7.333819

110 1 215.2 130.6 130.8 10.4 11.2 140.3 7.465903

111 1 215.2 130.4 130.3 8 11.5 139.2 1.776527

112 1 215.1 130.5 130.3 10.6 11.5 140.1 1.927405

113 1 215.4 130.7 131.1 9.7 11.8 140.6 2.87569

114 1 214.9 130.4 129.9 11.4 11 139.9 4.18792

115 1 215.1 130.3 130 10.6 10.8 139.7 1.133199

116 1 215.5 130.4 130 8.2 11.2 139.2 4.949746

117 1 214.7 130.6 130.1 11.8 10.5 139.8 2.076851

118 1 214.7 130.4 130.1 12.1 10.4 139.9 4.341875

119 1 214.8 130.5 130.2 11 11 140 6.873291

120 1 214.4 130.2 129.9 10.1 12 139.2 7.361863

121 1 214.8 130.3 130.4 10.1 12.1 139.6 6.160784

122 1 215.1 130.6 130.3 12.3 10.2 139.6 0.820162

123 1 215.3 130.8 131.1 11.6 10.6 140.2 8.199925

124 1 215.1 130.7 130.4 10.5 11.2 139.7 8.767972

125 1 214.7 130.5 130.5 9.9 10.3 140.1 4.518555

126 1 214.9 130 130.3 10.2 11.4 139.6 1.264342

127 1 215 130.4 130.4 9.4 11.6 140.2 8.712286

128 1 215.5 130.7 130.3 10.2 11.8 140 3.805659

129 1 215.1 130.2 130.2 10.1 11.3 140.3 1.132005

130 1 214.5 130.2 130.6 9.8 12.1 139.9 7.05902

131 1 214.3 130.2 130 10.7 10.5 139.8 0.147254

132 1 214.5 130.2 129.8 12.3 11.2 139.2 5.340653

133 1 214.9 130.5 130.2 10.6 11.5 139.9 1.035768

134 1 214.6 130.2 130.4 10.5 11.8 139.7 4.329426

135 1 214.2 130 130.2 11 11.2 139.5 7.190976

136 1 214.8 130.1 130.1 11.9 11.1 139.5 7.86245

137 1 214.6 129.8 130.2 10.7 11.1 139.4 6.169232

138 1 214.9 130.7 130.3 9.3 11.2 138.3 2.104685

139 1 214.6 130.4 130.4 11.3 10.8 139.8 1.850182

140 1 214.5 130.5 130.2 11.8 10.2 139.6 5.755739

141 1 214.8 130.2 130.3 10 11.9 139.3 0.750656

142 1 214.7 130 129.4 10.2 11 139.2 2.389343

143 1 214.6 130.2 130.4 11.2 10.7 139.9 6.203088

144 1 215 130.5 130.4 10.6 11.1 139.9 8.330734

145 1 214.5 129.8 129.8 11.4 10 139.3 8.650829

146 1 214.9 130.6 130.4 11.9 10.5 139.8 1.40345

147 1 215 130.5 130.4 11.4 10.7 139.9 7.332753

148 1 215.3 130.6 130.3 9.3 11.3 138.1 2.913333

149 1 214.7 130.2 130.1 10.7 11 139.4 4.863921

150 1 214.9 129.9 130 9.9 12.3 139.4 4.211332

151 1 214.9 130.3 129.9 11.9 10.6 139.8 0.956579

152 1 214.6 129.9 129.7 11.9 10.1 139 1.418857

153 1 214.6 129.7 129.3 10.4 11 139.3 6.479153

154 1 214.5 130.1 130.1 12.1 10.3 139.4 9.565215

155 1 214.5 130.3 130 11 11.5 139.5 8.19004

156 1 215.1 130 130.3 11.6 10.5 139.7 3.340708

157 1 214.2 129.7 129.6 10.3 11.4 139.5 4.539931

158 1 214.4 130.1 130 11.3 10.7 139.2 0.907883

159 1 214.8 130.4 130.6 12.5 10 139.3 5.111025

160 1 214.6 130.6 130.1 8.1 12.1 137.9 7.33093

161 1 215.6 130.1 129.7 7.4 12.2 138.4 5.010356

162 1 214.9 130.5 130.1 9.9 10.2 138.1 5.802157

163 1 214.6 130.1 130 11.5 10.6 139.5 1.915

164 1 214.7 130.1 130.2 11.6 10.9 139.1 4.298098

165 1 214.3 130.3 130 11.4 10.5 139.8 1.175106

166 1 215.1 130.3 130.6 10.3 12 139.7 8.925967

167 1 216.3 130.7 130.4 10 10.1 138.8 6.511685

168 1 215.6 130.4 130.1 9.6 11.2 138.6 5.318178

169 1 214.8 129.9 129.8 9.6 12 139.6 7.626296

170 1 214.9 130 129.9 11.4 10.9 139.7 9.92289

171 1 213.9 130.7 130.5 8.7 11.5 137.8 8.070468

172 1 214.2 130.6 130.4 12 10.2 139.6 3.852542

173 1 214.8 130.5 130.3 11.8 10.5 139.4 2.069325

174 1 214.8 129.6 130 10.4 11.6 139.2 0.986407

175 1 214.8 130.1 130 11.4 10.5 139.6 5.908994

176 1 214.9 130.4 130.2 11.9 10.7 139 7.349364

177 1 214.3 130.1 130.1 11.6 10.5 139.7 0.511428

178 1 214.5 130.4 130 9.9 12 139.6 5.119145

179 1 214.8 130.5 130.3 10.2 12.1 139.1 3.432399

180 1 214.5 130.2 130.4 8.2 11.8 137.8 8.753596

181 1 215 130.4 130.1 11.4 10.7 139.1 1.992127

182 1 214.8 130.6 130.6 8 11.4 138.7 9.226528

183 1 215 130.5 130.1 11 11.4 139.3 7.312417

184 1 214.6 130.5 130.4 10.1 11.4 139.3 6.073818

185 1 214.7 130.2 130.1 10.7 11.1 139.5 4.021342

186 1 214.7 130.4 130 11.5 10.7 139.4 7.331403

187 1 214.5 130.4 130 8 12.2 138.5 9.405799

188 1 214.8 130 129.7 11.4 10.6 139.2 7.806663

189 1 214.8 129.9 130.2 9.6 11.9 139.4 8.270527

190 1 214.6 130.3 130.2 12.7 9.1 139.2 6.934555

191 1 215.1 130.2 129.8 10.2 12 139.4 7.897621

192 1 215.4 130.5 130.6 8.8 11 138.6 1.874828

193 1 214.7 130.3 130.2 10.8 11.1 139.2 1.775244

194 1 215 130.5 130.3 9.6 11 138.5 2.938067

195 1 214.9 130.3 130.5 11.6 10.6 139.8 1.023377

196 1 215 130.4 130.3 9.9 12.1 139.6 0.022059

197 1 215.1 130.3 129.9 10.3 11.5 139.7 7.854284

198 1 214.8 130.3 130.4 10.6 11.1 140 3.595969

199 1 214.7 130.7 130.8 11.2 11.2 139.4 7.97424

200 1 214.3 129.9 129.9 10.2 11.5 139.6 0.224731

;

proc print;

run;

/* input obs Status length Left Rigth Bottom Top Diagonal Transpar; */

proc anova;

class Status;

model length Left Rigth Bottom Top Diagonal Transpar = Status;

means Status / tukey lines;

run;

Resultados do ANOVA e Tukey

arquivo para download

Resultados do SAS