ejemplos had

document.xlsx

Bajo Medio Alto Control34 41 32 4336 42 56 4242 38 53 4151 53 28 3738 43 43 5032 35 54 2636 37 52 33

269 289 318 272

document.xlsx

Nombre Altura Peso Sexo Test1 Test2 Test3 Test4 Test5Bill 74.2 176 1 90 86 134 65 9Mike 68.5 132 1 90 87 122 31 67Carol 65.0 157 0 82 75 145 2 6Scott 73.2 199 1 90 79 109 7 92Jill 65.8 154 0 100 92 132 79 73Francis 52.4 101 0 78 89 176 18 50Helen 69.2 157 0 90 84 103 64 87Marci 69.0 148 0 65 54 123 100 32Benedict 77.0 225 1 92 85 132 74 22Hank 71.0 179 1 70 60 144 36 78John 73.5 190 1 69 58 156 12 1Susan 66.9 155 0 80 86 157 68 22Gloria 67.1 190 0 89 77 98 23 25

Height Weight Sex Test1 Test2 Test3 Test4 Test5Height 1 0.8403123 0.670767 0.099593 -0.28053 -0.43736 0.227177 -0.10162Weight 0.8403123 1 0.518937 0.163474 -0.22444 -0.38447 0.003564 -0.17772Sex 0.6707673 0.5189366 1 0.003529 -0.15327 -0.01365 -0.21265 0.045212Test1 0.0995935 0.1634741 0.003529 1 0.83651 -0.44504 0.078383 0.289366Test2 -0.280526 -0.224444 -0.15327 0.83651 1 -0.02028 0.067272 0.209944Test3 -0.437357 -0.384469 -0.01365 -0.44504 -0.02028 1 -0.15146 -0.37462Test4 0.2271773 0.0035645 -0.21265 0.078383 0.067272 -0.15146 1 0.012659Test5 -0.101624 -0.177717 0.045212 0.289366 0.209944 -0.37462 0.012659 1

This technique uses formulas rather than the Analysis

ToolPak.

document.xlsx

Height Weight Sex Test1 Test2 Test3 Test4Height 1Weight 0.8403123 1Sex 0.6707673 0.5189366 1Test1 0.0995935 0.1634741 0.0035295 1Test2 -0.280526 -0.224444 -0.153271 0.8365099 1Test3 -0.437357 -0.384469 -0.01365 -0.445044 -0.020283 1Test4 0.2271773 0.0035645 -0.212653 0.0783833 0.0672719 -0.15146 1Test5 -0.101624 -0.177717 0.0452125 0.2893658 0.2099439 -0.374623 0.0126589

document.xlsx

Test5

1

Covarianza

Nombre Test1 Test2 Test3 Test4 Test5 Test1Bill 1 1 134 65 9 Test1 14Mike 2 2 122 31 67 Test2 14Carol 3 3 145 2 6 Test3 4.2307692Scott 4 4 109 7 92 Test4 10.572176Jill 5 5 132 79 73 Test5 -23.91756Francis 6 6 176 18 50Helen 7 7 103 64 87Marci 8 8 123 100 32Benedict 9 9 132 74 22Hank 10 10 144 36 78John 11 11 156 12 1Susan 12 12 157 68 22Gloria 13 13 98 23 25

Test1 Test2 Test3 Test4 Test5Test1 14 14 4.2307692 10.572176 -23.91756Test2 14 14 4.2307692 10.572176 -23.91756Test3 4.2307692 4.2307692 472.59172 -100.8166 -253.7264Test4 10.572176 10.572176 -100.8166 937.51721 12.075709Test5 -23.91756 -23.91756 -253.7264 12.075709 970.63696

This technique uses formulas rather than the Analysis ToolPak.

Covarianza

Test2 Test3 Test4 Test5

144.2307692 472.5917210.572176 -100.8166 937.51721-23.91756 -253.7264 12.075709 970.63696

document.xlsx

Muestra Costa Oeste Muestra Costa Este W. Coast Sample35 41 5232 35 29 Mean 39.2546 36 43 Standard Error 1.84800757 45 45 Median 37.545 44 28 Mode 3728 62 35 Standard Deviation 8.26454160 61 37 Sample Variance 68.3026337 62 32 Kurtosis 1.47266134 36 37 Skewness 1.18011433 52 41 Range 3237 46 54 Minimum 2832 52 44 Maximum 6038 38 42 Sum 78541 28 48 Count 20

38 50 46 3.86792542 52 4729 48 3940 38 4037 44 4144 50 47

Muestra región central

Confidence Level(95.0%)

document.xlsx

Midwest Sample E. Coast Sample

Mean 46 Mean 41.35Standard Error 2.10763 Standard Error 1.564869Median 45.5 Median 41.5Mode 52 Mode 37Standard Deviation 9.425609 Standard Deviation 6.998308Sample Variance 88.84211 Sample Variance 48.97632Kurtosis -0.47699 Kurtosis -0.28025Skewness 0.141207 Skewness -0.24858Range 34 Range 26Minimum 28 Minimum 28Maximum 62 Maximum 54Sum 920 Sum 827Count 20 Count 20

4.411322 3.27531Confidence Level(95.0%)

Confidence Level(95.0%)

This technique uses formulas rather than the Analysis ToolPak.

document.xlsx

Control Method2 Method2Mean 39.25 41.35 41.35Standard Error 1.848007462 1.56486925635137 1.564869256351Median 37.5 41.5 41.5Mode 37 37 37Standard Deviation 8.264540615 6.99830806620241 6.998308066202Variance 68.30263158 48.9763157894737 48.97631578947Kurtosis 1.472660678 -0.280253762688745 -0.28025376269Skewness 1.180113786 -0.24857926373299 -0.24857926373Range 32 26 26Minimum 28 28 28Maximum 60 54 54Sum 785 827 827Count 20 20 20Confidence Level (95%) 3.622028068 3.06708738296266 3.067087382963

Confidence Level 0.95 0.95 0.95

Suavidad exponencial

Mes ActualEnero 1,000 #N/AFebrero 1,455 1,000 Marzo 1,899 1318.5Abril 1,433 1724.85Mayo 1,900 1520.555Junio 2,133 1786.1665Julio 1,800 2028.9499Agosto 2,490 1868.685Septiembre 3,000 2303.6055Octubre 3,244 2791.0816Noviembre 4,598 3108.1245Diciembre 5,409 4151.0373

1 2 3 4 5 6 7 8 9 10 11 120

1,000

2,000

3,000

4,000

5,000

6,000 Suavidad Exponencial

ActualForecast

Punto Datos

Valo

r

Suavidad exponencial

1 2 3 4 5 6 7 8 9 10 11 120

1,000

2,000

3,000

4,000

5,000

6,000 Suavidad Exponencial

ActualForecast

Punto Datos

Valo

r

Prueba-F

Grupo 1 Grupo 2 Prueba-F para muestra de dos varianzas96 3978 53 Grupo 1 Grupo 272 51 Mean 75.444444 46.66666778 48 Variance 109.52778 2565 51 Observations 9 966 42 df 8 869 44 F 4.381111187 42 P(F<=f) one-tail 0.025855368 50 F Critical one-tail 3.4381031

document.xlsx

Datos62.7032 Bin Frecuencia Cumulative % Bin Frecuencia Cumulative %61.9644 32.74 1 .83% 53.08 24 20.00%48.4459 36.13 5 5.00% 56.47 21 37.50%46.4671 39.52 6 10.00% 49.69 16 50.83%55.0198 42.91 9 17.50% 59.86 16 64.17%59.1084 46.30 12 27.50% 46.30 12 74.17%54.5061 49.69 16 40.83% 42.91 9 81.67%

66.639 53.08 24 60.83% 63.25 9 89.17%53.0802 56.47 21 78.33% 39.52 6 94.17%43.1949 59.86 16 91.67% 36.13 5 98.33%

49.663 63.25 9 99.17% 32.74 1 99.17%51.4588 Más 1 100.00% Más 1 100.00%

55.92447.272155.257547.957554.418850.674951.156743.688260.519256.454861.660453.403162.579546.522461.796735.454361.407849.109246.801549.449748.753656.510951.6784

46.61341.525153.778842.832957.371550.044439.6795

53.08 56.47 49.69 59.86 46.30 42.91 63.25 39.52 36.13 32.740

5

10

15

20

25

30

0%

20%

40%

60%

80%

100%

120%Histograma

FrequencyCumulative %

Clase

Frec

uenc

ia

document.xlsx

53.555850.710553.889335.038935.003642.005443.789654.677152.423658.861246.631753.5903

55.76153.070352.943657.918357.974543.565537.584359.208640.0997

51.42752.441660.061639.326337.477140.872852.269756.191357.706443.831745.128448.7424

51.78858.858945.928545.427152.441657.113338.963758.525459.136536.3993

document.xlsx

53.95746.091442.222355.469740.444549.151743.675759.094456.628456.448952.901154.158858.852146.480651.9951

52.63438.199750.541742.696551.057854.683632.737945.2793

61.25152.148250.173533.558234.9176

44.88952.166

49.566851.094950.245756.824455.9304

document.xlsx

Medidas #N/A112 #N/A111 #N/A181 #N/A154 #N/A100 #N/A

87 #N/A193 #N/A170 #N/A

78 135.7171 138.5140 147.6202 144.6151 140108 142.4124 147.1134 147.2194 145.5153 149.2115 152.6205 144.2

56 140.2162 138129 143.3161 145.9150 147.9154 141125 132.2

65 130.9102 129.6192 144.2202 147.2192 148.3140 148.7165 144.9112 146165 148.9154 163.2208 167.9149 167.2185 165180 156.1103 168.5264 161.9

99 163.8131 162.9

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 960

50

100

150

200

250

300

Media móvil

ActualForecast

Punto datos

Valo

r

document.xlsx

156 161.4139 163.1225 163.7155 166.4212 167.1187 171.1143 168.6239 179.4207 182.7164 185.7186 184122 173.1116 173.2156 165.3133 163.4168 166.8177 151

81 150.4201 146.5125 142.7148 147.4169 152.7169 155179 158.9172 158.7166 161.5205 170.7173 175.6250 182.6195 183.4156 187.9214 197.1261 205.6264 205.9175 208.5192 205.8178 210.2217 206.5213 200.9139 202167 195.6150 187.4179 174.4134 171.8149 169.4168 173.4

document.xlsx

218 172.4207 171.4203 180.8233 189249 191170 192.1190 207.2285 220.6283

document.xlsx

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 960

50

100

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Media móvil

ActualForecast

Punto datos

Valo

r

Números aleatorios

Uniforme Normal Benoulli Binomial Poisson Discreta0.382000183 1.467033144 1 3 0 10.100680563 -1.18270918 1 3 0 10.596484268 0.329373506 1 3 2 10.899105808 -0.70603392 1 1 1 10.884609516 -1.45068043 1 3 0 10.958464309 -0.22961217 0 3 1 40.014496292 1.487419468 0 3 1 40.407422102 1.570383574 0 4 1 40.863246559 2.563865564 0 1 2 40.138584552 -0.30460569 1 1 1 40.245033113 -0.09303562 1 2 0 70.045472579 0.587413069 0 5 0 70.032380139 -0.19414756 1 4 0 70.164128544 0.79910933 0 1 4 70.219611194 -1.67898179 0 1 0 70.017090365 0.393392838 1 2 1 100.285042879 -0.92736173 0 5 1 100.343089084 -0.68337158 1 6 2 10

0.55363628 0.927052497 1 4 0 100.357371746 -0.28823365 0 0 0 100.371837519 1.053754204 0 4 1 10.355601672 -0.33571155 1 3 1 10.910306101 0.478581796 1 6 1 1

0.46601764 0.291862534 1 1 0 10.426160466 -0.83018904 0 2 1 10.303903317 2.50965968 1 2 0 40.975707266 1.130026703 0 2 0 40.806665242 -2.04940079 0 2 0 40.991241188 0.543964234 1 3 1 40.256263924 -0.33650849 0 1 2 40.951689199 0.617601472 1 2 1 7

0.05343791 -1.47256287 0 0 0 70.705038606 1.647867975 1 0 0 70.816522721 -0.81690132 0 2 0 70.972502823 -1.38430323 1 3 1 70.466322825 0.411577048 0 3 1 100.300210578 1.185248948 0 5 1 10

0.750206 0.613647444 0 1 0 100.351481674 -0.6728169 0 0 0 100.775658437 0.474611852 0 1 3 100.074343089 0.619058937 0 3 0 10.198431349 0.791117145 0 2 1 10.064058351 -0.77036248 1 2 0 10.358348338 -1.01450041 0 1 0 10.487044893 -1.01142177 0 2 2 1

Números aleatorios

0.511215552 -0.31953846 1 3 1 40.373455 0.639322479 0 4 1 4

0.985900449 1.417042768 0 4 0 40.040711692 1.101784619 1 3 1 40.230719932 0.38363396 0 4 1 40.004974517 0.587269824 0 3 1 70.926145207 1.64751782 0 0 1 70.100314341 1.060707291 1 1 3 70.256691183 1.583589437 1 4 1 70.775688955 1.371527105 1 6 0 70.679647206 -0.28297109 1 1 1 100.809106723 0.37793825 1 2 0 100.724326304 1.859734766 1 2 0 100.085055086 -0.73905426 1 2 1 10

0.13226722 -0.19589152 0 3 0 100.756157109 -1.36352355 0 2 0 10.626514481 -0.40467626 1 1 1 10.173650319 -0.20592324 1 4 1 1

0.40479751 0.176055437 1 2 0 10.552323984 1.667685865 0 3 2 1

0.71150853 1.077041816 1 2 1 40.555162206 -1.30235549 1 7 1 40.181157872 1.468015398 1 0 2 40.970274972 -0.18528226 1 2 3 4

0.68694113 1.326470738 0 2 0 40.528794214 -0.46062155 0 1 2 7

0.79668569 0.951079073 1 6 1 70.805658132 1.733865247 1 2 0 70.262215033 1.436201273 0 2 3 70.177953429 2.640590537 1 2 3 70.866756188 0.176573849 1 1 0 100.114841151 1.675889507 1 2 1 100.059511093 0.853697202 1 2 0 100.761558885 -1.68500264 1 4 0 100.738395337 1.391138085 1 4 2 100.986297189 2.238339221 0 3 2 10.925595874 -0.06797791 0 4 0 10.903866695 0.198904218 1 4 1 10.544969024 1.341686584 1 5 1 10.500778222 0.857128271 0 4 1 10.674977874 -0.32953494 0 3 1 40.489822077 0.204354365 1 4 2 4

0.14578692 0.978261596 0 1 0 40.037965026 0.981660833 1 3 0 40.796258431 -1.41606506 0 2 2 40.671559801 1.777343641 1 0 1 7

Números aleatorios

0.731681265 -0.22524091 0 3 1 70.584521012 0.31483296 1 3 0 70.152226325 -1.02017339 1 5 0 70.892178106 1.334819899 0 3 2 70.377819147 0.914601515 1 1 0 100.200476089 -0.08856659 1 1 1 100.205786309 -0.99266344 0 3 1 100.333964049 1.106573109 1 3 1 10

0.3251442 1.023340701 0 1 2

Jerarquía y Percentil

Comercial Ventas Punto Ventas Jerarquía PorcentajeAllen 137,676 4 197,107 1 100.00%Brandon 155,449 3 180,414 2 94.40%Campaigne 180,414 17 170,538 3 88.80%Dufenberg 197,107 14 161,750 4 83.30%Fox 130,814 2 155,449 5 77.70%Giles 133,283 11 151,466 6 72.20%Haflich 116,943 19 149,627 7 66.60%Hosaka 107,684 12 145,088 8 61.10%Jenson 128,060 1 137,676 9 55.50%Larson 121,336 18 134,395 10 50.00%Leitch 151,466 6 133,283 11 44.40%Miller 145,088 5 130,814 12 38.80%Peterson 127,995 9 128,060 13 33.30%Richards 161,750 13 127,995 14 27.70%Richardson 117,203 10 121,336 15 22.20%Ryan 102,571 15 117,203 16 16.60%Serrano 170,538 7 116,943 17 11.10%Struyk 134,395 8 107,684 18 5.50%Winfrey 149,627 16 102,571 19 .00%

Jerarquía y Percentil

Comercial Ventas Jerarquía PorcentajeAllen 137,676 9 55.56%Brandon 155,449 5 77.78%Campaigne 180,414 2 94.44%Dufenberg 197,107 1 100.00%Fox 130,814 12 38.89%Giles 133,283 11 44.44%Haflich 116,943 17 11.11%Hosaka 107,684 18 5.56%Jenson 128,060 13 33.33%Larson 121,336 15 22.22%Leitch 151,466 6 72.22%Miller 145,088 8 61.11%Peterson 127,995 14 27.78%Richards 161,750 4 83.33%Richardson 117,203 16 16.67%Ryan 102,571 19 0.00%Serrano 170,538 3 88.89%Struyk 134,395 10 50.00%Winfrey 149,627 7 66.67%

This technique uses formulas rather than the

Analysis ToolPak.

document.xlsx

Mes Adv bp Diff DepositosJan 4,927 10 2,071,149 RESUMEN SALIDAFeb 6,438 13 1,468,635Mar 5,616 6 1,780,402 Estadística RegresiónApr 10,672 12 2,349,637 Multiple R 0.7650994049May 11,283 -33 1,069,804 Raíz cuadrada 0.5853770994Jun 5,845 -31 732,188 Adjusted R Square 0.530094046Jul 4,911 -10 881,976 Error estándar 370049.27044Aug 375 -1 700,024 Observaciones 18Sep 7,656 3 1,391,848Oct 9,088 10 1,981,800 ANOVANov 5,545 14 2,469,982 df SSDec 4,551 14 1,759,743 Regression 2 2.899965E+12Jan 4,466 14 1,538,353 Residual 15 2.054047E+12Feb 5,524 13 1,442,750 Total 17 4.954012E+12Mar 5,927 19 1,547,134

Apr 5,494 11 1,320,301 Coeficientes Error estándarMay 3,283 0 948,765 Intercept 716434.66148 238757.33243Jun 5,678 9 818,945 Adv 107.68009435 36.207094986

bp Diff 25010.948657 6185.9241723

RESIDUAL OUTPUT

Observation Predicted Deposits Residuals1 1497083.9729 574065.02712 1734821.4414 -266186.44143 1471231.7633 309170.236734 2165728.0122 183908.987775 1106027.8603 -36223.86036 570485.40456 161702.595447 995142.11824 -113166.11828 731803.74821 -31779.748219 1615866.3098 -224018.3098

10 1945140.8455 36659.1545311 1663674.0658 806307.9341712 1556640.0521 203102.9479513 1547487.244 -9134.24403414 1636401.8352 -193651.835215 1829862.6052 -282728.605216 1583149.535 -262848.535

Regression analysis for bank deposits.

Adv = Amount spent on advertising. bp Diff = Interest rate paid, relative to competition (in basis points).Deposits = New deposits received.

document.xlsx

17 1069948.4112 -121183.411218 1552940.7751 -733995.7751

0 2,000 4,000 6,000 8,000 10,000 12,000

-1000000

-500000

0

500000

1000000

Adv Residual Plot

Adv

Res

idua

ls

-40 -30 -20 -10 0 10 20 30

-1000000

-500000

0

500000

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bp Diff Residual Plot

bp Diff

Res

idua

ls

0 5,000 10,000 15,0000

1,000,000

2,000,000

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Adv Line Fit Plot

Deposits

Predicted Deposits

Adv

Dep

osits

-40 -30 -20 -10 0 10 20 300

1,000,000

2,000,000

3,000,000

bp Diff Line Fit Plot

Deposits

Predicted Deposits

bp Diff

Dep

osits

0 20 40 60 80 100 1200

1000000

2000000

3000000

Normal Probability Plot

Sample Percentile

Dep

osits

document.xlsx

0 20 40 60 80 100 1200

1000000

2000000

3000000


Sample Percentile

Dep

osits

document.xlsx

MS F Significance F1.44998E+12 10.5887 0.00135641.36936E+11

t Stat P-value3.000681295 0.00896 207535.14 1225334.22.974005354 0.00946 30.506451 184.85374

4.04320324 0.00106 11825.955 38195.942

PROBABILITY OUTPUT

Standard Residuals Percentile Deposits1.551320521 2.7777778 700024-0.71932703 8.3333333 7321880.835483979 13.888889 8189450.496985138 19.444444 881976-0.09788929 25 9487650.436975853 30.555556 1069804-0.30581365 36.111111 1320301-0.08587978 41.666667 1391848-0.60537428 47.222222 14427500.099065604 52.777778 14686352.178920481 58.333333 15383530.548853799 63.888889 1547134-0.02468386 69.444444 1759743-0.52331365 75 1780402-0.76402962 80.555556 1981800-0.71030686 86.111111 2071149

Inferior 95%

Superior 95%

Regression analysis for bank deposits.

Adv = Amount spent on advertising. bp Diff = Interest rate paid, relative to competition (in basis points).Deposits = New deposits received.

document.xlsx

-0.32747912 91.666667 2349637-1.98350823 97.222222 2469982

0 2,000 4,000 6,000 8,000 10,000 12,000

-1000000

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Adv Residual Plot

Adv

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idua

ls

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bp Diff Residual Plot

bp Diff

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idua

ls

0 5,000 10,000 15,0000

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Adv Line Fit Plot

Deposits

Predicted Deposits

Adv

Dep

osits

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bp Diff Line Fit Plot

Deposits

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bp Diff

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osits

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Sample Percentile

Dep

osits

document.xlsx

0 20 40 60 80 100 1200

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2000000

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Sample Percentile

Dep

osits

Muestra

Population Población Muestra10.297968 7.6730464 12.389859 9.367032615.001421 8.6600073 7.0921249 9.4227755

9.700085 11.329965 9.2137975 7.121572110.461912 10.702285 10.690746 10.48573814.226285 13.924611 8.1449992 8.660007316.485388 12.363563 13.185532 4.5991849.8858607 11.420786 7.1632292 7.09212497.2703154 6.5021516 10.617678 13.43524311.912671 8.2376653 13.714381 8.66000737.1215721 10.886791 7.6577601 10.124617

4.765376 17.802919 10.4857388.6529508 12.851498 10.124617 8.8968302 Muestra media9.3670326 6.8296788 8.21352849.4586005 9.707411 7.374939113.448681 16.87829 13.2434515.9448996 12.263018 8.58431927.6150286 6.5253983 4.599184

13.3677 10.129818 7.489794613.435243 13.912319 9.42277559.8309363 4.286336 8.5396437

Población Media: 10.151426

document.xlsx

Estudiante Pretest Posttest t-Test: Paired Two Sample for Means1 71 692 63 61 Pretest3 68 70 Media 69.6190484 67 68 Varianza 16.6476195 66 61 Observaciones 216 63 60 Pearson Correlation 0.9627437 76 83 Diferencia Media Hipotética 08 70 72 df 209 69 71 t Stat -2.0815216

10 73 77 P(T<=t) one-tail 0.025222411 71 72 t Critical one-tail 1.72471812 66 66 P(T<=t) two-tail 0.050444813 70 71 t Critical two-tail 2.085962514 78 8615 68 7016 75 7817 65 6318 67 6819 71 7720 74 7821 71 72

document.xlsx

Posttest71.09523848.790476

21

document.xlsx

Estudiante Team-1 Team-2 z-Test: Two Sample for Means1 71 752 63 66 Team-1 Team-23 68 70 Media 69.619048 72.4285714 67 68 Varianza conocida 15.855 19.0075 66 67 Observaciones 21 216 63 68 Diferencia Media Hipotética 07 76 81 z -2.18055088 70 72 P(Z<=z) one-tail 0.01460839 69 71 z Critical one-tail 1.644853

10 73 77 P(Z<=z) two-tail 0.007304111 71 72 z Critical two-tail 1.959961112 66 6713 70 7914 78 7215 68 7316 75 7817 65 6918 67 6919 71 7720 74 7821 71 72

Media 69.619048 72.428571Varianza 15.854875 19.006803

ejemplos had

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