The following exercise needs to be done in R

The sample dat has the following format:

• dat$x[1] - mean value of normal distribution;
• dat$x[2] - standard deviation of normal distribution;
• dat$x[3] - intensity of exponential distribution;
• dat$x[4]:dat$x[503] sample from uniform distribution on [0.1].

Using this sample, create:

• Sample datNorm from normal distribution with mean dat$x[1] and standard deviation dat$x[2];
• Sample datExp from exponential distribution with intensity dat$x[3].

Create matrix res with the two samples:

res<-cbind(datNorm=datNorm,datExp=datExp)

x

0.80127

1.304686

2.46962

0.97271

0.819585

0.466901

0.114691

0.851757

0.538603

0.6815

0.161905

0.009867

0.172177

0.040116

0.856934

0.274749

0.625677

0.957054

0.060857

0.531776

0.165173

0.608313

0.482118

0.486537

0.864442

0.420642

0.740178

0.363181

0.876585

0.339098

0.458222

0.948976

0.081893

0.515661

0.845719

0.273579

0.795712

0.819177

0.901404

0.184256

0.260037

0.176934

0.499532

0.905204

0.025679

0.62413

0.752048

0.928287

0.608047

0.70257

0.028346

0.526764

0.11364

0.283705

0.647896

0.822867

0.202507

0.618452

0.069374

0.559248

0.852036

0.525438

0.885584

0.721796

0.873584

0.800988

0.212304

0.479053

0.762245

0.299262

0.505788

0.523226

0.856633

0.760083

0.435504

0.26589

0.231774

0.081514

0.611603

0.119174

0.423309

0.138191

0.939269

0.638936

0.609319

0.935327

0.220917

0.287205

0.941983

0.317701

0.903316

0.484125

0.519894

0.192691

0.338237

0.525004

0.574659

0.010628

0.844189

0.825011

0.793835

0.41342

0.700728

0.490989

0.070322

0.850569

0.246343

0.265007

0.353923

0.81314

0.874765

0.653059

0.621492

0.315182

0.10591

0.463833

0.53286

0.592468

0.998962

0.765071

0.148365

0.358217

0.995457

0.629075

0.411707

0.914978

0.609482

0.506612

0.910195

0.495058

0.149754

0.228465

0.350993

0.857104

0.857438

0.73333

0.03285

0.207579

0.288753

0.842559

0.71464

0.15527

0.987194

0.16726

0.378429

0.79111

0.917239

0.385145

0.334227

0.919408

0.256208

0.963243

0.373023

0.300742

0.471378

0.466694

0.272879

0.325992

0.453326

0.844759

0.360638

0.414462

0.91021

0.776567

0.265603

0.833099

0.645869

0.086922

0.355671

0.177182

0.358973

0.964515

0.780292

0.536637

0.093021

0.595379

0.986559

0.693905

0.863274

0.674411

0.438217

0.616458

0.861261

0.271545

0.327704

0.296797

0.655145

0.580479

0.290077

0.640126

0.27554

0.007884

0.657554

0.449353

0.733458

0.301393

0.845132

0.829295

0.177767

0.052363

0.85786

0.406013

0.380034

0.851261

0.655431

0.06378

0.674556

0.0747

0.081466

0.543238

0.058828

0.475777

0.814218

0.822982

0.767174

0.522571

0.979856

0.333368

0.139469

0.806106

0.233353

0.727824

0.814936

0.134999

0.800642

0.638079

0.357343

0.855781

0.684867

0.327865

0.288716

0.286111

0.458734

0.152406

0.977375

0.55269

0.011714

0.51541

0.337935

0.180955

0.269395

0.442922

0.21887

0.290104

0.097171

0.649466

0.661431

0.827252

0.791359

0.477301

0.511279

0.454808

0.425437

0.762791

0.597326

0.206154

0.824208

0.433364

0.199931

0.32421

0.046965

0.66583

0.271698

0.567198

0.851753

0.647831

0.714147

0.937388

0.350188

0.142977

0.106605

0.740063

0.828275

0.8051

0.094532

0.370059

0.978736

0.006104

0.607868

0.714096

0.128502

0.07445

0.045043

0.327775

0.814541

0.959311

0.422326

0.636353

0.001116

0.097424

0.63464

0.017103

0.990396

0.837436

0.549384

0.754834

0.505256

0.812407

0.560398

0.783002

0.586586

0.35164

0.267108

0.618168

0.319598

0.737732

0.55807

0.328621

0.712989

0.574828

0.638786

0.555476

0.128592

0.611519

0.656602

0.767763

0.665508

0.609949

0.684687

0.474876

0.955855

0.232217

0.210615

0.302566

0.560095

0.485507

0.243151

0.796338

0.084949

0.436729

0.13444

0.433292

0.425555

0.064677

0.435426

0.922196

0.071921

0.865445

0.987245

0.718316

0.978654

0.246887

0.945538

0.113462

0.698422

0.843268

0.944482

0.234611

0.06049

0.153938

0.436467

0.087278

0.145067

0.843911

0.94793

0.358547

0.118963

0.681426

0.492825

0.505794

0.464157

0.665745

0.393373

0.575666

0.315618

0.099298

0.028815

0.186584

0.652092

0.778045

0.433389

0.173286

0.233977

0.709077

0.548591

0.964446

0.646061

0.786859

0.553691

0.885404

0.131545

0.645618

0.047408

0.801319

0.546274

0.088499

0.255256

0.382478

0.479302

0.372747

0.123076

0.565028

0.706369

0.181125

0.447888

0.813228

0.259128

0.050302

0.844033

0.026559

0.401529

0.175379

0.895266

0.424306

0.021431

0.977458

0.53142

0.661144

0.273537

0.090194

0.771291

0.173095

0.40684

0.375074

0.488995

0.552789

0.994946

0.36861

0.845404

0.602319

0.920484

0.508997

0.616064

0.345622

0.8092

0.283123

0.457436

0.311458

0.614395

0.854942

0.567364

0.388121

0.142343

0.27564

0.137159

0.368999

0.403841

0.872627

0.376894

0.987078

0.294347

0.155073

0.745832

0.457889

0.877609

0.596887

0.885984

0.971996

0.237426

0.664221

0.734333

0.978179

0.571958

0.018317

0.918351

0.485676

0.305344

0.858371

0.277956

0.580075

0.984293

0.132021

0.233598

0.381096

0.136641

0.536578

0.498756

0.4984

0.067679

0.471878

0.57248

0.903036

0.093013

0.680384

0.551911

0.265059

0.709929

0.786233

0.279192

0.68978

0.70655

0.412281

0.070242

0.76921

0.581835

0.853056

0.435933

0.696547

0.275486

0.833613

0.730049

0.234851

0.647188

0.760662

0.700471

0.600731

0.107578

0.844982

0.254037

0.20436

0.233674

0.680998

0.677578