logistic regression

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Logistic regression

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Logistic regression. Recall the simple linear regression model: y = b 0 + b 1 x + e. where we are trying to predict a continuous dependent variable y from a continuous independent variable x. This model can be extended to Multiple linear regression model: - PowerPoint PPT Presentation

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  • Logistic regression

  • Recall the simple linear regression model:y = b0 + b1x + ewhere we are trying to predict a continuous dependent variable y from a continuous independent variable x.This model can be extended to Multiple linear regression model:y = b0 + b1x1 + b2x2 + + + bpxp + eHere we are trying to predict a continuous dependent variable y from a several continuous dependent variables x1 , x2 , , xp .

  • Now suppose the dependent variable y is binary. It takes on two values Success (1) or Failure (0)This is the situation in which Logistic Regression is usedWe are interested in predicting a y from a continuous dependent variable x.

  • ExampleWe are interested how the success (y) of a new antibiotic cream is curing acne problems and how it depends on the amount (x) that is applied daily.The values of y are 1 (Success) or 0 (Failure).The values of x range over a continuum

  • The logisitic Regression ModelLet p denote P[y = 1] = P[Success].This quantity will increase with the value of x. The ratio: is called the odds ratio This quantity will also increase with the value of x, ranging from zero to infinity. The quantity: is called the log odds ratio

  • Example: odds ratio, log odds ratioSuppose a die is rolled:Success = roll a six, p = 1/6The odds ratio The log odds ratio

  • The logisitic Regression Modeli. e. : In terms of the odds ratio Assumes the log odds ratio is linearly related to x.

  • The logisitic Regression Modelor Solving for p in terms x.

  • Interpretation of the parameter b0 (determines the intercept)p x

    Chart3

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    Sheet2

    Sheet3

  • Interpretation of the parameter b1 (determines when p is 0.50 (along with b0))p x when

    Chart3

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    Sheet3

  • Alsowhenis the rate of increase in p with respect to x when p = 0.50

  • Interpretation of the parameter b1 (determines slope when p is 0.50 )p x

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  • The dataThe data will for each case consist ofa value for x, the continuous independent variablea value for y (1 or 0) (Success or Failure)Total of n = 250 cases

  • Sheet2 (2)

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    2054.010.880797078

    2060.900.2497398944

    2070.700.214165017

    2080.900.2497398944

    2090.300.1544652651

    2102.010.5

    2114.510.92414182

    2121.500.3775406688

    2133.510.8175744762

    2142.510.6224593312

    2150.500.1824255238

    2164.210.9002495109

    2170.300.1544652651

    2184.210.9002495109

    2194.310.908877039

    2200.000.119202922

    2213.400.8021838886

    2221.710.4255574832

    2230.400.1679816149

    2242.810.6899744811

    2253.900.8698915256

    2264.210.9002495109

    2273.610.8320183851

    2282.010.5

    2294.710.9370266439

    2302.410.5986876601

    2313.310.785834983

    2323.510.8175744762

    2330.610.1978161114

    2340.700.214165017

    2352.910.7109495026

    2361.300.3318122278

    2372.600.6456563062

    2382.500.6224593312

    2390.100.1301084744

    2403.010.7310585786

    2411.300.3318122278

    2421.010.2689414214

    2430.010.119202922

    2442.000.5

    2453.810.8581489351

    2460.300.1544652651

    2474.010.880797078

    2480.000.119202922

    2494.310.908877039

    2504.510.92414182

    Sheet3

  • Estimation of the parametersThe parameters are estimated by Maximum Likelihood estimation and require a statistical package such as SPSS

  • Using SPSS to perform Logistic regressionOpen the data file:

  • Choose from the menu: Analyze -> Regression -> Binary Logistic

  • The following dialogue box appearsSelect the dependent variable (y) and the independent variable (x) (covariate).Press OK.

  • Here is the outputThe Estimates and their S.E.

  • The parameter Estimates

    Sheet1

    bSE

    X1.03090.1334

    Constant-2.04750.332

    Sheet2

    Sheet3

    Sheet1

    bSE

    X1.03090.1334

    Constant-2.04750.332

    1.0309

    -2.0475

    Sheet2

    Sheet3

  • Interpretation of the parameter b0 (determines the intercept)Interpretation of the parameter b1 (determines when p is 0.50 (along with b0))

  • Another interpretation of the parameter b1is the rate of increase in p with respect to x when p = 0.50

  • Nonparametric Statistical Methods

  • DefinitionWhen the data is generated from process (model) that is known except for finite number of unknown parameters the model is called a parametric model.

    Otherwise, the model is called a non-parametric modelStatistical techniques that assume a non-parametric model are called non-parametric.

  • Example Parametric modelNormal distribution known except for the two parameters m and s.

    sm

    Chart1

    0.000514093

    0.0006405993

    0.0007946961

    0.000981489

    0.0012068121

    0.0014772828

    0.0018003521

    0.002184344

    0.0026384839

    0.0031729092

    0.003798662

    0.0045276564

    0.0053726194

    0.0063469998

    0.0074648434

    0.0087406297

    0.0101890699

    0.0118248643

    0.0136624187

    0.0157155222

    0.0179969888

    0.0205182671

    0.0232890254

    0.0263167194

    0.0296061537

    0.0331590463

    0.0369736116

    0.041044174

    0.0453608275

    0.0499091552

    0.0546700249

    0.0596194722

    0.064728685

    0.0699640987

    0.0752876092

    0.0806569082

    0.086025942

    0.0913454891

    0.0965638509

    0.1016276423

    0.1064826685

    0.1110748676

    0.1153512977

    0.1192611431

    0.1227567134

    0.1257944092

    0.1283356249

    0.1303475647

    0.131803947

    0.1326855754

    0.1329807601

    0.1326855754

    0.131803947

    0.1303475647

    0.1283356249

    0.1257944092

    0.1227567134

    0.1192611431

    0.1153512977

    0.1110748676

    0.1064826685

    0.1016276423

    0.0965638509

    0.0913454891

    0.086025942

    0.0806569082

    0.0752876092

    0.0699640987

    0.064728685

    0.0596194722

    0.0546700249

    0.0499091552

    0.0453608275

    0.041044174

    0.0369736116

    0.0331590463

    0.0296061537

    0.0263167194

    0.0232890254

    0.0205182671

    0.0179969888

    0.0157155222

    0.0136624187

    0.0118248643

    0.0101890699

    0.0087406297

    0.0074648434

    0.0063469998

    0.0053726194

    0.0045276564

    0.003798662

    0.0031729092

    0.0026384839

    0.002184344

    0.0018003521

    0.0014772828

    0.0012068121

    0.000981489

    0.0007946961

    0.0006405993

    0.000514093

    Sheet1

    00.00051409300.0011349982

    0.20.00064059930.00226209350.0012294051

    0.40.00079469610.00818730750.0013313929

    0.60.0009814890.016668410.001441541

    0.80.00120681210.02681280180.0015604701

    10.00147728280.03790816620.0016888444

    1.20.00180035210.04939304730.0018273746

    1.40.0021843440.06083169970.0019768204

    1.60.00263848390.07189263430.0021379937

    1.80.00317290920.08233035610.0023117614

    20.0037986620.09196986030.0024990485

    2.20.00452765640.10069350280.0027008417

    2.40.00537261940.10842991630.0029181923

    2.60.00634699980.11514468260.00315222

    2.80.00746484340.12083251230.0034041161

    30.00874062970.12551071510.0036751474

    3.20.01018906990.12921377150.0039666596

    3.40.01182486430.13198884610.0042800811

    3.60.01366241870.13389209950.0046169265

    3.80.01571552220.13498567890.0049788007

    40.01799698880.13533528330.005367402

    4.20.02051826710.13500821220.0057845261

    4.40.02328902540.13407182160.006232069

    4.60.02631671940.13259232080.0067120309

    4.80.02960615370.13063385280.0072265187

    50.03315904630.12825781040.007777749

    5.20.03697361160.12552234720.0083680503

    5.40.0410441740.1224820470.0089998653

    5.60.04536082750.11918772280.0096757521

    5.80.04990915520.11568632020.0103983848

    60.05467002490.11202090380.0111705541

    6.20.05961947220.10823070880.0119951661

    6.40.0647286850.10435124220.0128752407

    6.60.06996409870.10041442330.0138139088

    6.80.07528760920.09644875020.0148144079

    70.08065690820.09247948670.0158800765

    7.20.0860259420.08852886070.0170143465

    7.40.09134548910.08461626940.0182207342

    7.60.09656385090.08075848640.0195028284

    7.80.10162764230.07696986830.020864277

    80.10648266850.07326255560.0223087696

    8.20.11107486760.06964666840.0238400185

    8.40.11535129770.06613049380.0254617354

    8.60.11926114310.0627206640.0271776044

    8.80.12275671340.05942232510.0289912515

    90.12579440920.0562392950.030906209

    9.20.12833562490.05317421110.0329258751

    9.40.13034756470.05022866780.0350534682

    9.60.1318039470.0474033430.0372919755

    9.80.13268557540.04469811490.0396440945

    100.13298076010.04211216870.0421121687

    10.20.13268557540.03964409450.0446981149

    10.40.1318039470.03729197550.047403343

    10.60.13034756470.03505346820.0502286678

    10.80.12833562490.03292587510.0531742111

    110.12579440920.0309062090.056239295

    11.20.12275671340.02899125150.0594223251

    11.40.11926114310.02717760440.062720664

    11.60.11535129770.02546173540.0661304938

    11.80.11107486760.02384001850.0696466684

    120.10648266850.02230876960.0732625556

    12.20.10162764230.0208642770.0769698683

    12.40.09656385090.01950282840.0807584864

    12.60.09134548910.01822073420.0846162694

    12.80.0860259420.01701434650.0885288607

    130.08065690820.01588007650.0924794867

    13.20.07528760920.01481440790.0964487502

    13.40.06996409870.01381390880.1004144233

    13.60.0647286850.01287524070.1043512422

    13.80.05961947220.01199516610.1082307088

    140.05467002490.01117055410.1120209038

    14.20.04990915520.01039838480.1156863202

    14.40.04536082750.00967575210.1191877228

    14.60.0410441740.00899986530.122482047

    14.80.03697361160.00836805030.1255223472

    150.03315904630.0077777490.1282578104

    15.20.02960615370.00722651870.1306338528

    15.40.02631671940.00671203090.1325923208

    15.60.02328902540.0062320690.1340718216

    15.80.02051826710.00578452610.1350082122

    160.01799698880.0053674020.1353352833

    16.20.01571552220.00497880070.1349856789

    16.40.01366241870.00461692650.1338920995

    16.60.01182486430.00428008110.1319888461

    16.80.01018906990.00396665960.1292137715

    170.00874062970.00367514740.1255107151

    17.20.00746484340.00340411610.1208325123

    17.40.00634699980.003152220.1151446826

    17.60.00537261940.00291819230.1084299163

    17.80.00452765640.00270084170.1006935028

    180.0037986620.00249904850.0919698603

    18.20.00317290920.00231176140.0823303561

    18.40.00263848390.00213799370.0718926343

    18.60.0021843440.00197682040.0608316997

    18.80.00180035210.00182737460.0493930473

    190.00147728280.00168884440.0379081662

    19.20.00120681210.00156047010.0268128018

    19.40.0009814890.0014415410.01666841

    19.60.00079469610.00133139290.0081873075

    19.80.00064059930.00122940510.0022620935

    200.0005140930.00113499820

    Sheet1

    Sheet2

    Sheet3

  • Example Non parametric modelNo assumptions are made about the distribution could be normal, skewed bimodal etc

  • The sign testA nonparametric test for the central location of a distribution

  • We want to test:H0: median = m0HA: median m0against(or against a one-sided alternative)

  • The Sign test:S = the number of observations that exceed m0Comment: If H0: median = m0 is true we would expect 50% of the observations to be above m0, and 50% of the observations to be below m0, The test statistic:

  • If H 0 is true then S will have a binomial distribution with p = 0.50, n = sample size.50%50%median = m0

    Chart5

    0.0048681898

    0.0085315612

    0.0144442537

    0.0235865744

    0.0371080024

    0.0562068907

    0.0819264245

    0.1148785605

    0.154937933

    0.2009775396

    0.2507348748

    0.3008888179

    0.3473881218

    0.3860074367

    0.413034492

    0.4259377637

    0.4238506014

    0.4077452195

    0.3802491416

    0.3451519701

    0.3067295224

    0.2690497878

    0.2522307747

    0

    0.2522307747

    0.2354117617

    0.2080138622

    0.1878762468

    0.1749763288

    0.1685172178

    0.1672403067

    0.1697099359

    0.174527753

    0.1804645118

    0.1865191584

    0.1919261269

    0.1961332489

    0.1987682207

    0.1996049704

    0.1985352168

    0.1955462895

    0.1907040486

    0.1841390315

    0.1760341501

    0.1666128375

    0.1561271524

    0.1448458382

    0.1330426447

    0.1209853683

    0.1089260903

    0.097093028

    0.0856842962

    0.0748637329

    0.0647587978

    0.0554604173

    0.0470245387

    0.0394750792

    0.0328079074

    0.0269954833

    0.021991798

    0.0177372964

    0.0141635189

    0.0111972651

    0.0087641502

    0.0067914846

    0.0052104674

    0.0039577258

    0.0029762662

    0.0022159242

    0.0016334095

    0.0011920441

    0.0008612845

    0.0006161096

    0.0004363413

    Bimodal

    00.00486818980.0007913203msw

    0.10.00853156120.00144608573.510.5

    0.20.01444425370.00257235221.50.50.5

    0.30.02358657440.0044423655

    0.40.03710800240.0074355351

    0.50.05620689070.0120500146

    0.60.08192642450.0188980728

    0.70.11487856050.02867724

    0.80.1549379330.0421118672

    0.90.20097753960.0598654768

    10.25073487480.0824324698

    1.10.30088881790.1100264314

    1.20.34738812180.142488573

    1.30.38600743670.1792408512

    1.40.4130344920.2193023351

    1.50.42593776370.2613750309

    1.60.42385060140.30398809

    1.70.40774521950.3456759811

    1.80.38024914160.3851561834

    1.90.34515197010.4214719778

    20.30672952240.4540759845

    2.10.26904978780.4828434898

    2.150.2522307747

    2.150

    2.150.2522307747

    2.20.23541176170.5080219191

    2.30.20801386220.5301352211

    2.40.18787624680.549867918

    2.50.17497632880.5679525989

    2.60.16851721780.5850783464

    2.70.16724030670.6018289025

    2.80.16970993590.6186511784

    2.90.1745277530.6358489371

    30.18046451180.6535937827

    3.10.18651915840.6719455507

    3.20.19192612690.6908758309

    3.30.19613324890.7102905836

    3.40.19876822070.730049866

    3.50.19960497040.7499841569

    3.60.19853521680.7699072707

    3.70.19554628950.7896271351

    3.80.19070404860.8089546214

    3.90.18413903150.8277104511

    40.17603415010.8457310901

    4.10.16661283750.8628734176

    4.20.15612715240.8790181941

    4.30.14484583820.8940723277

    4.40.13304264470.9079699525

    4.50.12098536830.9206723696

    4.60.10892609030.9321669491

    4.70.0970930280.9424651341

    4.80.08568429620.9515997252

    4.90.07486373290.9596216444

    50.06475879780.9665963856

    5.10.0554604173

    5.20.0470245387

    5.30.0394750792

    5.40.0328079074

    5.50.0269954833

    5.60.021991798

    5.70.0177372964

    5.80.0141635189

    5.90.0111972651

    60.0087641502

    6.10.0067914846

    6.20.0052104674

    6.30.0039577258

    6.40.0029762662

    6.50.0022159242

    6.60.0016334095

    6.70.0011920441

    6.80.0008612845

    6.90.0006161096

    70.0004363413

    Bimodal

    Positively Skewed

    00088

    0.050.1572514170.99809254

    0.10.150.36528311740.9823673983

    0.20.250.54112728590.9458390865

    0.30.350.65023111490.8917263579

    0.40.450.69724257820.8267032464

    0.50.550.69863640890.7569789886

    0.60.650.67076831950.6871153477

    0.70.750.62631923520.6200385158

    0.80.850.57406592220.5574065923

    0.90.950.51965391140.5

    11.050.46648743270.4480346089

    1.11.150.41646425490.4013858656

    1.21.250.37051285510.3597394402

    1.31.350.32896154620.3226881546

    1.41.450.29178271080.289792

    1.51.550.25875001440.260613729

    1.61.650.22953717480.2347387275

    1.71.750.20377840430.21178501

    1.81.850.18110416040.1914071696

    1.91.950.16116124230.1732967536

    22.050.1436231250.1571806293

    2.12.150.1281943340.1428183168

    2.22.250.11461128630.1299988834

    2.32.350.10264112730.1185377548

    2.42.450.0920795190.1082736421

    2.52.550.0827479610.0990656902

    2.62.650.07449099320.0907908941

    2.72.750.06717347730.0833417948

    2.82.850.06067806390.076624447

    2.92.950.05490289330.0705566406

    33.050.04975954550.0650663513

    3.13.150.04517123310.0600903967

    3.23.250.04107122320.0555732734

    3.33.350.03740146620.0514661511

    3.43.450.03411140970.0477260045

    3.53.550.0311569760.0443148635

    3.63.650.02849968090.0411991659

    3.73.750.02610587680.0383491978

    3.83.850.02394610160.0357386102

    3.93.950.02199451920.033344

    44.050.02022843890.0311445481

    4.14.150.01862790130.0291217042

    4.24.250.01717532250.0272589141

    4.34.350.01585518740.0255413818

    4.44.450.01465378530.0239558631

    4.54.550.01355898120.0224904845

    4.64.650.01256001850.0211345864

    4.74.750.01164734810.0198785846

    4.84.850.01081248030.0187138498

    4.90.0176326017

    5

    Positively Skewed

    Negaitively Skewed

    00000.010812480388

    10.050.1572514170.01164734810.99809254

    20.10.150.36528311740.01256001850.9823673983

    30.20.250.54112728590.01355898120.9458390865

    40.30.350.65023111490.01465378530.8917263579

    50.40.450.69724257820.01585518740.8267032464

    60.50.550.69863640890.01717532250.7569789886

    70.60.650.67076831950.01862790130.6871153477

    80.70.750.62631923520.02022843890.6200385158

    90.80.850.57406592220.02199451920.5574065923

    100.90.950.51965391140.02394610160.5

    1111.050.46648743270.02610587680.4480346089

    121.11.150.41646425490.02849968090.4013858656

    131.21.250.37051285510.0311569760.3597394402

    141.31.350.32896154620.03411140970.3226881546

    151.41.450.29178271080.03740146620.289792

    161.51.550.25875001440.04107122320.260613729

    171.61.650.22953717480.04517123310.2347387275

    181.71.750.20377840430.04975954550.21178501

    191.81.850.18110416040.05490289330.1914071696

    201.91.950.16116124230.06067806390.1732967536

    2122.050.1436231250.06717347730.1571806293

    222.12.150.1281943340.07449099320.1428183168

    232.22.250.11461128630.0827479610.1299988834

    242.32.350.10264112730.0920795190.1185377548

    252.42.450.0920795190.10264112730.1082736421

    262.52.550.0827479610.11461128630.0990656902

    272.62.650.07449099320.1281943340.0907908941

    282.72.750.06717347730.1436231250.0833417948

    292.82.850.06067806390.16116124230.076624447

    302.92.950.05490289330.18110416040.0705566406

    3133.050.04975954550.20377840430.0650663513

    323.13.150.04517123310.22953717480.0600903967

    333.23.250.04107122320.25875001440.0555732734

    343.33.350.03740146620.29178271080.0514661511

    353.43.450.03411140970.32896154620.0477260045

    363.53.550.0311569760.37051285510.0443148635

    373.63.650.02849968090.41646425490.0411991659

    383.73.750.02610587680.46648743270.0383491978

    393.83.850.02394610160.51965391140.0357386102

    403.93.950.02199451920.57406592220.033344

    4144.050.02022843890.62631923520.0311445481

    424.14.150.01862790130.67076831950.0291217042

    434.24.250.01717532250.69863640890.0272589141

    444.34.350.01585518740.69724257820.0255413818

    454.44.450.01465378530.65023111490.0239558631

    464.54.550.01355898120.54112728590.0224904845

    474.64.650.01256001850.36528311740.0211345864

    484.74.750.01164734810.1572514170.0198785846

    494.84.850.010812480300.0187138498

    4.90.0176326017

    5

    Negaitively Skewed

    0.0108124803

    0.0116473481

    0.0125600185

    0.0135589812

    0.0146537853

    0.0158551874

    0.0171753225

    0.0186279013

    0.0202284389

    0.0219945192

    0.0239461016

    0.0261058768

    0.0284996809

    0.031156976

    0.0341114097

    0.0374014662

    0.0410712232

    0.0451712331

    0.0497595455

    0.0549028933

    0.0606780639

    0.0671734773

    0.0744909932

    0.082747961

    0.092079519

    0.1026411273

    0.1146112863

    0.128194334

    0.143623125

    0.1611612423

    0.1811041604

    0.2037784043

    0.2295371748

    0.2587500144

    0.2917827108

    0.3289615462

    0.3705128551

    0.4164642549

    0.4664874327

    0.5196539114

    0.5740659222

    0.6263192352

    0.6707683195

    0.6986364089

    0.6972425782

    0.6502311149

    0.5411272859

    0.3652831174

    0.157251417

    0

    Normal

    00.0175283005msw

    0.10.02239453032.510.5

    0.20.02832703772.510.5

    0.30.0354745928

    0.40.043983596

    0.50.0539909665

    0.60.0656158148

    0.70.0789501583

    0.80.0940490774

    0.90.1109208347

    10.1295175957

    1.10.1497274656

    1.20.171368592

    1.30.194186055

    1.40.217852177

    1.50.2419707245

    1.60.2660852499

    1.70.2896915528

    1.80.3122539334

    1.90.3332246029

    20.3520653268

    2.10.3682701403

    2.20.3813878155

    2.30.391042694

    2.40.3969525475

    2.50.3989422804

    2.60.3969525475

    2.70.391042694

    2.80.3813878155

    2.90.3682701403

    30.3520653268

    3.10.3332246029

    3.20.3122539334

    3.30.2896915528

    3.40.2660852499

    3.50.2419707245

    3.60.217852177

    3.70.194186055

    3.80.171368592

    3.90.1497274656

    40.1295175957

    4.10.1109208347

    4.20.0940490774

    4.30.0789501583

    4.40.0656158148

    4.50.0539909665

    4.60.043983596

    4.70.0354745928

    4.80.0283270377

    4.90.0223945303

    50.0175283005

    Normal

  • If H 0 is not true then S will still have a binomial distribution. However p will not be equal to 0.50.medianm0pm0 > median p < 0.50

  • medianm0pm0 < median p > 0.50p = the probability that an observation is greater than m0.

  • Summarizing: If H 0 is true then S will have a binomial distribution with p = 0.50, n = sample size.n = 10

    Chart3

    0.0009765625

    0.009765625

    0.0439453125

    0.1171875

    0.205078125

    0.24609375

    0.205078125

    0.1171875

    0.0439453125

    0.009765625

    0.0009765625

    Sheet1

    00.00097656250.5

    10.009765625

    20.0439453125

    30.1171875

    40.205078125

    50.24609375

    60.205078125

    70.1171875

    80.0439453125

    90.009765625

    100.0009765625

    Sheet1

    Bimodal

    00.00486818980.0007913203msw

    0.10.00853156120.00144608573.510.5

    0.20.01444425370.00257235221.50.50.5

    0.30.02358657440.0044423655

    0.40.03710800240.0074355351

    0.50.05620689070.0120500146

    0.60.08192642450.0188980728

    0.70.11487856050.02867724

    0.70

    0.70.1148785605

    0.80.1549379330.0421118672

    0.90.20097753960.0598654768

    10.25073487480.0824324698

    1.10.30088881790.1100264314

    1.20.34738812180.142488573

    1.30.38600743670.1792408512

    1.40.4130344920.2193023351

    1.50.42593776370.2613750309

    1.60.42385060140.30398809

    1.70.40774521950.3456759811

    1.80.38024914160.3851561834

    1.90.34515197010.4214719778

    20.30672952240.4540759845

    2.10.26904978780.4828434898

    2.150.2522307747

    2.150

    2.150.2522307747

    2.20.23541176170.5080219191

    2.30.20801386220.5301352211

    2.40.18787624680.549867918

    2.50.17497632880.5679525989

    2.60.16851721780.5850783464

    2.70.16724030670.6018289025

    2.80.16970993590.6186511784

    2.90.1745277530.6358489371

    30.18046451180.6535937827

    3.10.18651915840.6719455507

    3.20.19192612690.6908758309

    3.30.19613324890.7102905836

    3.40.19876822070.730049866

    3.50.19960497040.7499841569

    3.60.19853521680.7699072707

    3.70.19554628950.7896271351

    3.80.19070404860.8089546214

    3.90.18413903150.8277104511

    40.17603415010.8457310901

    4.10.16661283750.8628734176

    4.20.15612715240.8790181941

    4.30.14484583820.8940723277

    4.40.13304264470.9079699525

    4.50.12098536830.9206723696

    4.60.10892609030.9321669491

    4.70.0970930280.9424651341

    4.80.08568429620.9515997252

    4.90.07486373290.9596216444

    50.06475879780.9665963856

    5.10.0554604173

    5.20.0470245387

    5.30.0394750792

    5.40.0328079074

    5.50.0269954833

    5.60.021991798

    5.70.0177372964

    5.80.0141635189

    5.90.0111972651

    60.0087641502

    6.10.0067914846

    6.20.0052104674

    6.30.0039577258

    6.40.0029762662

    6.50.0022159242

    6.60.0016334095

    6.70.0011920441

    6.80.0008612845

    6.90.0006161096

    70.0004363413

    Bimodal

    Positively Skewed

    00088

    0.050.1572514170.99809254

    0.10.150.36528311740.9823673983

    0.20.250.54112728590.9458390865

    0.30.350.65023111490.8917263579

    0.40.450.69724257820.8267032464

    0.50.550.69863640890.7569789886

    0.60.650.67076831950.6871153477

    0.70.750.62631923520.6200385158

    0.80.850.57406592220.5574065923

    0.90.950.51965391140.5

    11.050.46648743270.4480346089

    1.11.150.41646425490.4013858656

    1.21.250.37051285510.3597394402

    1.31.350.32896154620.3226881546

    1.41.450.29178271080.289792

    1.51.550.25875001440.260613729

    1.61.650.22953717480.2347387275

    1.71.750.20377840430.21178501

    1.81.850.18110416040.1914071696

    1.91.950.16116124230.1732967536

    22.050.1436231250.1571806293

    2.12.150.1281943340.1428183168

    2.22.250.11461128630.1299988834

    2.32.350.10264112730.1185377548

    2.42.450.0920795190.1082736421

    2.52.550.0827479610.0990656902

    2.62.650.07449099320.0907908941

    2.72.750.06717347730.0833417948

    2.82.850.06067806390.076624447

    2.92.950.05490289330.0705566406

    33.050.04975954550.0650663513

    3.13.150.04517123310.0600903967

    3.23.250.04107122320.0555732734

    3.33.350.03740146620.0514661511

    3.43.450.03411140970.0477260045

    3.53.550.0311569760.0443148635

    3.63.650.02849968090.0411991659

    3.73.750.02610587680.0383491978

    3.83.850.02394610160.0357386102

    3.93.950.02199451920.033344

    44.050.02022843890.0311445481

    4.14.150.01862790130.0291217042

    4.24.250.01717532250.0272589141

    4.34.350.01585518740.0255413818

    4.44.450.01465378530.0239558631

    4.54.550.01355898120.0224904845

    4.64.650.01256001850.0211345864

    4.74.750.01164734810.0198785846

    4.84.850.01081248030.0187138498

    4.90.0176326017

    5

    Positively Skewed

    0

    0.157251417

    0.3652831174

    0.5411272859

    0.6502311149

    0.6972425782

    0.6986364089

    0.6707683195

    0.6263192352

    0.5740659222

    0.5196539114

    0.4664874327

    0.4164642549

    0.3705128551

    0.3289615462

    0.2917827108

    0.2587500144

    0.2295371748

    0.2037784043

    0.1811041604

    0.1611612423

    0.143623125

    0.128194334

    0.1146112863

    0.1026411273

    0.092079519

    0.082747961

    0.0744909932

    0.0671734773

    0.0606780639

    0.0549028933

    0.0497595455

    0.0451712331

    0.0410712232

    0.0374014662

    0.0341114097

    0.031156976

    0.0284996809

    0.0261058768

    0.0239461016

    0.0219945192

    0.0202284389

    0.0186279013

    0.0171753225

    0.0158551874

    0.0146537853

    0.0135589812

    0.0125600185

    0.0116473481

    0.0108124803

    Negaitively Skewed

    00000.010812480388

    10.050.1572514170.01164734810.99809254

    20.10.150.36528311740.01256001850.9823673983

    30.20.250.54112728590.01355898120.9458390865

    40.30.350.65023111490.01465378530.8917263579

    50.40.450.69724257820.01585518740.8267032464

    60.50.550.69863640890.01717532250.7569789886

    70.60.650.67076831950.01862790130.6871153477

    80.70.750.62631923520.02022843890.6200385158

    90.80.850.57406592220.02199451920.5574065923

    100.90.950.51965391140.02394610160.5

    1111.050.46648743270.02610587680.4480346089

    121.11.150.41646425490.02849968090.4013858656

    131.21.250.37051285510.0311569760.3597394402

    141.31.350.32896154620.03411140970.3226881546

    151.41.450.29178271080.03740146620.289792

    161.51.550.25875001440.04107122320.260613729

    171.61.650.22953717480.04517123310.2347387275

    181.71.750.20377840430.04975954550.21178501

    191.81.850.18110416040.05490289330.1914071696

    201.91.950.16116124230.06067806390.1732967536

    2122.050.1436231250.06717347730.1571806293

    222.12.150.1281943340.07449099320.1428183168

    232.22.250.11461128630.0827479610.1299988834

    242.32.350.10264112730.0920795190.1185377548

    252.42.450.0920795190.10264112730.1082736421

    262.52.550.0827479610.11461128630.0990656902

    272.62.650.07449099320.1281943340.0907908941

    282.72.750.06717347730.1436231250.0833417948

    292.82.850.06067806390.16116124230.076624447

    302.92.950.05490289330.18110416040.0705566406

    3133.050.04975954550.20377840430.0650663513

    323.13.150.04517123310.22953717480.0600903967

    333.23.250.04107122320.25875001440.0555732734

    343.33.350.03740146620.29178271080.0514661511

    353.43.450.03411140970.32896154620.0477260045

    363.53.550.0311569760.37051285510.0443148635

    373.63.650.02849968090.41646425490.0411991659

    383.73.750.02610587680.46648743270.0383491978

    393.83.850.02394610160.51965391140.0357386102

    403.93.950.02199451920.57406592220.033344

    4144.050.02022843890.62631923520.0311445481

    424.14.150.01862790130.67076831950.0291217042

    434.24.250.01717532250.69863640890.0272589141

    444.34.350.01585518740.69724257820.0255413818

    454.44.450.01465378530.65023111490.0239558631

    464.54.550.01355898120.54112728590.0224904845

    474.64.650.01256001850.36528311740.0211345864

    484.74.750.01164734810.1572514170.0198785846

    494.84.850.010812480300.0187138498

    4.90.0176326017

    5

    Negaitively Skewed

    0.0108124803

    0.0116473481

    0.0125600185

    0.0135589812

    0.0146537853

    0.0158551874

    0.0171753225

    0.0186279013

    0.0202284389

    0.0219945192

    0.0239461016

    0.0261058768

    0.0284996809

    0.031156976

    0.0341114097

    0.0374014662

    0.0410712232

    0.0451712331

    0.0497595455

    0.0549028933

    0.0606780639

    0.0671734773

    0.0744909932

    0.082747961

    0.092079519

    0.1026411273

    0.1146112863

    0.128194334

    0.143623125

    0.1611612423

    0.1811041604

    0.2037784043

    0.2295371748

    0.2587500144

    0.2917827108

    0.3289615462

    0.3705128551

    0.4164642549

    0.4664874327

    0.5196539114

    0.5740659222

    0.6263192352

    0.6707683195

    0.6986364089

    0.6972425782

    0.6502311149

    0.5411272859

    0.3652831174

    0.157251417

    0

    Normal

    00.0175283005msw

    0.10.02239453032.510.5

    0.20.02832703772.510.5

    0.30.0354745928

    0.40.043983596

    0.50.0539909665

    0.60.0656158148

    0.70.0789501583

    0.80.0940490774

    0.90.1109208347

    10.1295175957

    1.10.1497274656

    1.20.171368592

    1.30.194186055

    1.40.217852177

    1.50.2419707245

    1.60.2660852499

    1.70.2896915528

    1.80.3122539334

    1.90.3332246029

    20.3520653268

    2.10.3682701403

    2.20.3813878155

    2.30.391042694

    2.40.3969525475

    2.50.3989422804

    2.50

    2.50.3989422804

    2.60.3969525475

    2.70.391042694

    2.80.3813878155

    2.90.3682701403

    30.3520653268

    3.10.3332246029

    3.20.3122539334

    3.30.2896915528

    3.40.2660852499

    3.50.2419707245

    3.60.217852177

    3.70.194186055

    3.80.171368592

    3.90.1497274656

    40.1295175957

    4.10.1109208347

    4.20.0940490774

    4.30.0789501583

    4.40.0656158148

    4.50.0539909665

    4.60.043983596

    4.70.0354745928

    4.80.0283270377

    4.90.0223945303

    50.0175283005

    Normal

    0.0175283005

    0.0223945303

    0.0283270377

    0.0354745928

    0.043983596

    0.0539909665

    0.0656158148

    0.0789501583

    0.0940490774

    0.1109208347

    0.1295175957

    0.1497274656

    0.171368592

    0.194186055

    0.217852177

    0.2419707245

    0.2660852499

    0.2896915528

    0.3122539334

    0.3332246029

    0.3520653268

    0.3682701403

    0.3813878155

    0.391042694

    0.3969525475

    0.3989422804

    0

    0.3989422804

    0.3969525475

    0.391042694

    0.3813878155

    0.3682701403

    0.3520653268

    0.3332246029

    0.3122539334

    0.2896915528

    0.2660852499

    0.2419707245

    0.217852177

    0.194186055

    0.171368592

    0.1497274656

    0.1295175957

    0.1109208347

    0.0940490774

    0.0789501583

    0.0656158148

    0.0539909665

    0.043983596

    0.0354745928

    0.0283270377

    0.0223945303

    0.0175283005

    Sheet1

    0.5

    xp(x)

    00.0010

    10.0098

    20.0439

    30.1172

    40.2051

    50.2461

    60.2051

    70.1172

    80.0439

    90.0098

    100.0010

    Sheet1

    Bimodal

    00.00486818980.0007913203msw

    0.10.00853156120.00144608573.510.5

    0.20.01444425370.00257235221.50.50.5

    0.30.02358657440.0044423655

    0.40.03710800240.0074355351

    0.50.05620689070.0120500146

    0.60.08192642450.0188980728

    0.70.11487856050.02867724

    0.70

    0.70.1148785605

    0.80.1549379330.0421118672

    0.90.20097753960.0598654768

    10.25073487480.0824324698

    1.10.30088881790.1100264314

    1.20.34738812180.142488573

    1.30.38600743670.1792408512

    1.40.4130344920.2193023351

    1.50.42593776370.2613750309

    1.60.42385060140.30398809

    1.70.40774521950.3456759811

    1.80.38024914160.3851561834

    1.90.34515197010.4214719778

    20.30672952240.4540759845

    2.10.26904978780.4828434898

    2.150.2522307747

    2.150

    2.150.2522307747

    2.20.23541176170.5080219191

    2.30.20801386220.5301352211

    2.40.18787624680.549867918

    2.50.17497632880.5679525989

    2.60.16851721780.5850783464

    2.70.16724030670.6018289025

    2.80.16970993590.6186511784

    2.90.1745277530.6358489371

    30.18046451180.6535937827

    3.10.18651915840.6719455507

    3.20.19192612690.6908758309

    3.30.19613324890.7102905836

    3.40.19876822070.730049866

    3.50.19960497040.7499841569

    3.60.19853521680.7699072707

    3.70.19554628950.7896271351

    3.80.19070404860.8089546214

    3.90.18413903150.8277104511

    40.17603415010.8457310901

    4.10.16661283750.8628734176

    4.20.15612715240.8790181941

    4.30.14484583820.8940723277

    4.40.13304264470.9079699525

    4.50.12098536830.9206723696

    4.60.10892609030.9321669491

    4.70.0970930280.9424651341

    4.80.08568429620.9515997252

    4.90.07486373290.9596216444

    50.06475879780.9665963856

    5.10.0554604173

    5.20.0470245387

    5.30.0394750792

    5.40.0328079074

    5.50.0269954833

    5.60.021991798

    5.70.0177372964

    5.80.0141635189

    5.90.0111972651

    60.0087641502

    6.10.0067914846

    6.20.0052104674

    6.30.0039577258

    6.40.0029762662

    6.50.0022159242

    6.60.0016334095

    6.70.0011920441

    6.80.0008612845

    6.90.0006161096

    70.0004363413

    Bimodal

    Positively Skewed

    00088

    0.050.1572514170.99809254

    0.10.150.36528311740.9823673983

    0.20.250.54112728590.9458390865

    0.30.350.65023111490.8917263579

    0.40.450.69724257820.8267032464

    0.50.550.69863640890.7569789886

    0.60.650.67076831950.6871153477

    0.70.750.62631923520.6200385158

    0.80.850.57406592220.5574065923

    0.90.950.51965391140.5

    11.050.46648743270.4480346089

    1.11.150.41646425490.4013858656

    1.21.250.37051285510.3597394402

    1.31.350.32896154620.3226881546

    1.41.450.29178271080.289792

    1.51.550.25875001440.260613729

    1.61.650.22953717480.2347387275

    1.71.750.20377840430.21178501

    1.81.850.18110416040.1914071696

    1.91.950.16116124230.1732967536

    22.050.1436231250.1571806293

    2.12.150.1281943340.1428183168

    2.22.250.11461128630.1299988834

    2.32.350.10264112730.1185377548

    2.42.450.0920795190.1082736421

    2.52.550.0827479610.0990656902

    2.62.650.07449099320.0907908941

    2.72.750.06717347730.0833417948

    2.82.850.06067806390.076624447

    2.92.950.05490289330.0705566406

    33.050.04975954550.0650663513

    3.13.150.04517123310.0600903967

    3.23.250.04107122320.0555732734

    3.33.350.03740146620.0514661511

    3.43.450.03411140970.0477260045

    3.53.550.0311569760.0443148635

    3.63.650.02849968090.0411991659

    3.73.750.02610587680.0383491978

    3.83.850.02394610160.0357386102

    3.93.950.02199451920.033344

    44.050.02022843890.0311445481

    4.14.150.01862790130.0291217042

    4.24.250.01717532250.0272589141

    4.34.350.01585518740.0255413818

    4.44.450.01465378530.0239558631

    4.54.550.01355898120.0224904845

    4.64.650.01256001850.0211345864

    4.74.750.01164734810.0198785846

    4.84.850.01081248030.0187138498

    4.90.0176326017

    5

    Positively Skewed

    0

    0.157251417

    0.3652831174

    0.5411272859

    0.6502311149

    0.6972425782

    0.6986364089

    0.6707683195

    0.6263192352

    0.5740659222

    0.5196539114

    0.4664874327

    0.4164642549

    0.3705128551

    0.3289615462

    0.2917827108

    0.2587500144

    0.2295371748

    0.2037784043

    0.1811041604

    0.1611612423

    0.143623125

    0.128194334

    0.1146112863

    0.1026411273

    0.092079519

    0.082747961

    0.0744909932

    0.0671734773

    0.0606780639

    0.0549028933

    0.0497595455

    0.0451712331

    0.0410712232

    0.0374014662

    0.0341114097

    0.031156976

    0.0284996809

    0.0261058768

    0.0239461016

    0.0219945192

    0.0202284389

    0.0186279013

    0.0171753225

    0.0158551874

    0.0146537853

    0.0135589812

    0.0125600185

    0.0116473481

    0.0108124803

    Negaitively Skewed

    00000.010812480388

    10.050.1572514170.01164734810.99809254

    20.10.150.36528311740.01256001850.9823673983

    30.20.250.54112728590.01355898120.9458390865

    40.30.350.65023111490.01465378530.8917263579

    50.40.450.69724257820.01585518740.8267032464

    60.50.550.69863640890.01717532250.7569789886

    70.60.650.67076831950.01862790130.6871153477

    80.70.750.62631923520.02022843890.6200385158

    90.80.850.57406592220.02199451920.5574065923

    100.90.950.51965391140.02394610160.5

    1111.050.46648743270.02610587680.4480346089

    121.11.150.41646425490.02849968090.4013858656

    131.21.250.37051285510.0311569760.3597394402

    141.31.350.32896154620.03411140970.3226881546

    151.41.450.29178271080.03740146620.289792

    161.51.550.25875001440.04107122320.260613729

    171.61.650.22953717480.04517123310.2347387275

    181.71.750.20377840430.04975954550.21178501

    191.81.850.18110416040.05490289330.1914071696

    201.91.950.16116124230.06067806390.1732967536

    2122.050.1436231250.06717347730.1571806293

    222.12.150.1281943340.07449099320.1428183168

    232.22.250.11461128630.0827479610.1299988834

    242.32.350.10264112730.0920795190.1185377548

    252.42.450.0920795190.10264112730.1082736421

    262.52.550.0827479610.11461128630.0990656902

    272.62.650.07449099320.1281943340.0907908941

    282.72.750.06717347730.1436231250.0833417948

    292.82.850.06067806390.16116124230.076624447

    302.92.950.05490289330.18110416040.0705566406

    3133.050.04975954550.20377840430.0650663513

    323.13.150.04517123310.22953717480.0600903967

    333.23.250.04107122320.25875001440.0555732734

    343.33.350.03740146620.29178271080.0514661511

    353.43.450.03411140970.32896154620.0477260045

    363.53.550.0311569760.37051285510.0443148635

    373.63.650.02849968090.41646425490.0411991659

    383.73.750.02610587680.46648743270.0383491978

    393.83.850.02394610160.51965391140.0357386102

    403.93.950.02199451920.57406592220.033344

    4144.050.02022843890.62631923520.0311445481

    424.14.150.01862790130.67076831950.0291217042

    434.24.250.01717532250.69863640890.0272589141

    444.34.350.01585518740.69724257820.0255413818

    454.44.450.01465378530.65023111490.0239558631

    464.54.550.01355898120.54112728590.0224904845

    474.64.650.01256001850.36528311740.0211345864

    484.74.750.01164734810.1572514170.0198785846

    494.84.850.010812480300.0187138498

    4.90.0176326017

    5

    Negaitively Skewed

    0.0108124803

    0.0116473481

    0.0125600185

    0.0135589812

    0.0146537853

    0.0158551874

    0.0171753225

    0.0186279013

    0.0202284389

    0.0219945192

    0.0239461016

    0.0261058768

    0.0284996809

    0.031156976

    0.0341114097

    0.0374014662

    0.0410712232

    0.0451712331

    0.0497595455

    0.0549028933

    0.0606780639

    0.0671734773

    0.0744909932

    0.082747961

    0.092079519

    0.1026411273

    0.1146112863

    0.128194334

    0.143623125

    0.1611612423

    0.1811041604

    0.2037784043

    0.2295371748

    0.2587500144

    0.2917827108

    0.3289615462

    0.3705128551

    0.4164642549

    0.4664874327

    0.5196539114

    0.5740659222

    0.6263192352

    0.6707683195

    0.6986364089

    0.6972425782

    0.6502311149

    0.5411272859

    0.3652831174

    0.157251417

    0

    Normal

    00.0175283005msw

    0.10.02239453032.510.5

    0.20.02832703772.510.5

    0.30.0354745928

    0.40.043983596

    0.50.0539909665

    0.60.0656158148

    0.70.0789501583

    0.80.0940490774

    0.90.1109208347

    10.1295175957

    1.10.1497274656

    1.20.171368592

    1.30.194186055

    1.40.217852177

    1.50.2419707245

    1.60.2660852499

    1.70.2896915528

    1.80.3122539334

    1.90.3332246029

    20.3520653268

    2.10.3682701403

    2.20.3813878155

    2.30.391042694

    2.40.3969525475

    2.50.3989422804

    2.50

    2.50.3989422804

    2.60.3969525475

    2.70.391042694

    2.80.3813878155

    2.90.3682701403

    30.3520653268

    3.10.3332246029

    3.20.3122539334

    3.30.2896915528

    3.40.2660852499

    3.50.2419707245

    3.60.217852177

    3.70.194186055

    3.80.171368592

    3.90.1497274656

    40.1295175957

    4.10.1109208347

    4.20.0940490774

    4.30.0789501583

    4.40.0656158148

    4.50.0539909665

    4.60.043983596

    4.70.0354745928

    4.80.0283270377

    4.90.0223945303

    50.0175283005

    Normal

    0.0175283005

    0.0223945303

    0.0283270377

    0.0354745928

    0.043983596

    0.0539909665

    0.0656158148

    0.0789501583

    0.0940490774

    0.1109208347

    0.1295175957

    0.1497274656

    0.171368592

    0.194186055

    0.217852177

    0.2419707245

    0.2660852499

    0.2896915528

    0.3122539334

    0.3332246029

    0.3520653268

    0.3682701403

    0.3813878155

    0.391042694

    0.3969525475

    0.3989422804

    0

    0.3989422804

    0.3969525475

    0.391042694

    0.3813878155

    0.3682701403

    0.3520653268

    0.3332246029

    0.3122539334

    0.2896915528

    0.2660852499

    0.2419707245

    0.217852177

    0.194186055

    0.171368592

    0.1497274656

    0.1295175957

    0.1109208347

    0.0940490774

    0.0789501583

    0.0656158148

    0.0539909665

    0.043983596

    0.0354745928

    0.0283270377

    0.0223945303

    0.0175283005

  • The critical and acceptance region:n = 10Choose the critical region so that a is close to 0.05 or 0.01.e. g. If critical region is {0,1,9,10} then a = .0010 + .0098 + .0098 +.0010 = .0216

    Sheet1

    0.5

    xp(x)

    00.0010

    10.0098

    20.0439

    30.1172

    40.2051

    50.2461

    60.2051

    70.1172

    80.0439

    90.0098

    100.0010

    Sheet1

    Bimodal

    00.00486818980.0007913203msw

    0.10.00853156120.00144608573.510.5

    0.20.01444425370.00257235221.50.50.5

    0.30.02358657440.0044423655

    0.40.03710800240.0074355351

    0.50.05620689070.0120500146

    0.60.08192642450.0188980728

    0.70.11487856050.02867724

    0.70

    0.70.1148785605

    0.80.1549379330.0421118672

    0.90.20097753960.0598654768

    10.25073487480.0824324698

    1.10.30088881790.1100264314

    1.20.34738812180.142488573

    1.30.38600743670.1792408512

    1.40.4130344920.2193023351

    1.50.42593776370.2613750309

    1.60.42385060140.30398809

    1.70.40774521950.3456759811

    1.80.38024914160.3851561834

    1.90.34515197010.4214719778

    20.30672952240.4540759845

    2.10.26904978780.4828434898

    2.150.2522307747

    2.150

    2.150.2522307747

    2.20.23541176170.5080219191

    2.30.20801386220.5301352211

    2.40.18787624680.549867918

    2.50.17497632880.5679525989

    2.60.16851721780.5850783464

    2.70.16724030670.6018289025

    2.80.16970993590.6186511784

    2.90.1745277530.6358489371

    30.18046451180.6535937827

    3.10.18651915840.6719455507

    3.20.19192612690.6908758309

    3.30.19613324890.7102905836

    3.40.19876822070.730049866

    3.50.19960497040.7499841569

    3.60.19853521680.7699072707

    3.70.19554628950.7896271351

    3.80.19070404860.8089546214

    3.90.18413903150.8277104511

    40.17603415010.8457310901

    4.10.16661283750.8628734176

    4.20.15612715240.8790181941

    4.30.14484583820.8940723277

    4.40.13304264470.9079699525

    4.50.12098536830.9206723696

    4.60.10892609030.9321669491

    4.70.0970930280.9424651341

    4.80.08568429620.9515997252

    4.90.07486373290.9596216444

    50.06475879780.9665963856

    5.10.0554604173

    5.20.0470245387

    5.30.0394750792

    5.40.0328079074

    5.50.0269954833

    5.60.021991798

    5.70.0177372964

    5.80.0141635189

    5.90.0111972651

    60.0087641502

    6.10.0067914846

    6.20.0052104674

    6.30.0039577258

    6.40.0029762662

    6.50.0022159242

    6.60.0016334095

    6.70.0011920441

    6.80.0008612845

    6.90.0006161096

    70.0004363413

    Bimodal

    Positively Skewed

    00088

    0.050.1572514170.99809254

    0.10.150.36528311740.9823673983

    0.20.250.54112728590.9458390865

    0.30.350.65023111490.8917263579

    0.40.450.69724257820.8267032464

    0.50.550.69863640890.7569789886

    0.60.650.67076831950.6871153477

    0.70.750.62631923520.6200385158

    0.80.850.57406592220.5574065923

    0.90.950.51965391140.5

    11.050.46648743270.4480346089

    1.11.150.41646425490.4013858656

    1.21.250.37051285510.3597394402

    1.31.350.32896154620.3226881546

    1.41.450.29178271080.289792

    1.51.550.25875001440.260613729

    1.61.650.22953717480.2347387275

    1.71.750.20377840430.21178501

    1.81.850.18110416040.1914071696

    1.91.950.16116124230.1732967536

    22.050.1436231250.1571806293

    2.12.150.1281943340.1428183168

    2.22.250.11461128630.1299988834

    2.32.350.10264112730.1185377548

    2.42.450.0920795190.1082736421

    2.52.550.0827479610.0990656902

    2.62.650.07449099320.0907908941

    2.72.750.06717347730.0833417948

    2.82.850.06067806390.076624447

    2.92.950.05490289330.0705566406

    33.050.04975954550.0650663513

    3.13.150.04517123310.0600903967

    3.23.250.04107122320.0555732734

    3.33.350.03740146620.0514661511

    3.43.450.03411140970.0477260045

    3.53.550.0311569760.0443148635

    3.63.650.02849968090.0411991659

    3.73.750.02610587680.0383491978

    3.83.850.02394610160.0357386102

    3.93.950.02199451920.033344

    44.050.02022843890.0311445481

    4.14.150.01862790130.0291217042

    4.24.250.01717532250.0272589141

    4.34.350.01585518740.0255413818

    4.44.450.01465378530.0239558631

    4.54.550.01355898120.0224904845

    4.64.650.01256001850.0211345864

    4.74.750.01164734810.0198785846

    4.84.850.01081248030.0187138498

    4.90.0176326017

    5

    Positively Skewed

    0

    0.157251417

    0.3652831174

    0.5411272859

    0.6502311149

    0.6972425782

    0.6986364089

    0.6707683195

    0.6263192352

    0.5740659222

    0.5196539114

    0.4664874327

    0.4164642549

    0.3705128551

    0.3289615462

    0.2917827108

    0.2587500144

    0.2295371748

    0.2037784043

    0.1811041604

    0.1611612423

    0.143623125

    0.128194334

    0.1146112863

    0.1026411273

    0.092079519

    0.082747961

    0.0744909932

    0.0671734773

    0.0606780639

    0.0549028933

    0.0497595455

    0.0451712331

    0.0410712232

    0.0374014662

    0.0341114097

    0.031156976

    0.0284996809

    0.0261058768

    0.0239461016

    0.0219945192

    0.0202284389

    0.0186279013

    0.0171753225

    0.0158551874

    0.0146537853

    0.0135589812

    0.0125600185

    0.0116473481

    0.0108124803

    Negaitively Skewed

    00000.010812480388

    10.050.1572514170.01164734810.99809254

    20.10.150.36528311740.01256001850.9823673983

    30.20.250.54112728590.01355898120.9458390865

    40.30.350.65023111490.01465378530.8917263579

    50.40.450.69724257820.01585518740.8267032464

    60.50.550.69863640890.01717532250.7569789886

    70.60.650.67076831950.01862790130.6871153477

    80.70.750.62631923520.02022843890.6200385158

    90.80.850.57406592220.02199451920.5574065923

    100.90.950.51965391140.02394610160.5

    1111.050.46648743270.02610587680.4480346089

    121.11.150.41646425490.02849968090.4013858656

    131.21.250.37051285510.0311569760.3597394402

    141.31.350.32896154620.03411140970.3226881546

    151.41.450.29178271080.03740146620.289792

    161.51.550.25875001440.04107122320.260613729

    171.61.650.22953717480.04517123310.2347387275

    181.71.750.20377840430.04975954550.21178501

    191.81.850.18110416040.05490289330.1914071696

    201.91.950.16116124230.06067806390.1732967536

    2122.050.1436231250.06717347730.1571806293

    222.12.150.1281943340.07449099320.1428183168

    232.22.250.11461128630.0827479610.1299988834

    242.32.350.10264112730.0920795190.1185377548

    252.42.450.0920795190.10264112730.1082736421

    262.52.550.0827479610.11461128630.0990656902

    272.62.650.07449099320.1281943340.0907908941

    282.72.750.06717347730.1436231250.0833417948

    292.82.850.06067806390.16116124230.076624447

    302.92.950.05490289330.18110416040.0705566406

    3133.050.04975954550.20377840430.0650663513

    323.13.150.04517123310.22953717480.0600903967

    333.23.250.04107122320.25875001440.0555732734

    343.33.350.03740146620.29178271080.0514661511

    353.43.450.03411140970.32896154620.0477260045

    363.53.550.0311569760.37051285510.0443148635

    373.63.650.02849968090.41646425490.0411991659

    383.73.750.02610587680.46648743270.0383491978

    393.83.850.02394610160.51965391140.0357386102

    403.93.950.02199451920.57406592220.033344

    4144.050.02022843890.62631923520.0311445481

    424.14.150.01862790130.67076831950.0291217042

    434.24.250.01717532250.69863640890.0272589141

    444.34.350.01585518740.69724257820.0255413818

    454.44.450.01465378530.65023111490.0239558631

    464.54.550.01355898120.54112728590.0224904845

    474.64.650.01256001850.36528311740.0211345864

    484.74.750.01164734810.1572514170.0198785846

    494.84.850.010812480300.0187138498

    4.90.0176326017

    5

    Negaitively Skewed

    0.0108124803

    0.0116473481

    0.0125600185

    0.0135589812

    0.0146537853

    0.0158551874

    0.0171753225

    0.0186279013

    0.0202284389

    0.0219945192

    0.0239461016

    0.0261058768

    0.0284996809

    0.031156976

    0.0341114097

    0.0374014662

    0.0410712232

    0.0451712331

    0.0497595455

    0.0549028933

    0.0606780639

    0.0671734773

    0.0744909932

    0.082747961

    0.092079519

    0.1026411273

    0.1146112863

    0.128194334

    0.143623125

    0.1611612423

    0.1811041604

    0.2037784043

    0.2295371748

    0.2587500144

    0.2917827108

    0.3289615462

    0.3705128551

    0.4164642549

    0.4664874327

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    0

    Normal

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    0.10.02239453032.510.5

    0.20.02832703772.510.5

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    2.50

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    2.90.3682701403

    30.3520653268

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    50.0175283005

    Normal

    0.0175283005

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    0.0354745928

    0.043983596

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    Chart4

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    Sheet1

    0.5

    xp(x)

    00.0010

    10.0098

    20.0439

    30.1172

    40.2051

    50.2461

    60.2051

    70.1172

    80.0439

    90.0098

    100.0010

    Sheet1

    Bimodal

    00.00486818980.0007913203msw

    0.10.00853156120.00144608573.510.5

    0.20.01444425370.00257235221.50.50.5

    0.30.02358657440.0044423655

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