Knowledge (XXG)

Outcome (probability)

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39: 534: 522: 813: 391:(or informally, "groups") of outcomes. For comparison, we could define an event to occur when "at least one 'heads'" is flipped in the experiment - that is, when the outcome contains at least one 'heads'. This event would contain all outcomes in the sample space except the element (T, T). 584:
Some treatments of probability assume that the various outcomes of an experiment are always defined so as to be equally likely. However, there are experiments that are not easily described by a set of equally likely outcomes— for example, if one were to toss a
553:). For example, when tossing an ordinary coin, one typically assumes that the outcomes "head" and "tail" are equally likely to occur. An implicit assumption that all outcomes are equally likely underpins most 330: 507: 470:
Some "mixed" distributions contain both stretches of continuous outcomes and some discrete outcomes; the discrete outcomes in such distributions can be called
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Since individual outcomes may be of little practical interest, or because there may be prohibitively (even infinitely) many of them, outcomes are grouped into
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many times and observe whether it landed with its point upward or downward, there is no symmetry to suggest that the two outcomes should be equally likely.
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are (H, T), (T, H), (T, T) and (H, H), where "H" represents a "heads", and "T" represents a "tails". Outcomes should not be confused with
485:, the probability of an outcome need not even be defined. In particular, the set of events on which probability is defined may be some 792: 757: 703: 467:
distribution, individual outcomes all have zero probability, and non-zero probabilities can only be assigned to ranges of outcomes.
366:(only one outcome will occur on each trial of the experiment). All of the possible outcomes of an experiment form the elements of a 316: 304: 263: 817: 359: 194: 130: 242: 103: 435:
of the sample space are defined as events). However, this approach does not work well in cases where the sample space is
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Typically, when the sample space is finite, any subset of the sample space is an event (that is, all elements of the
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it is possible, and often necessary, to exclude certain subsets of the sample space from being events.
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or trial. Each possible outcome of a particular experiment is unique, and different outcomes are
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Outcomes may occur with probabilities that are between zero and one (inclusively). In a
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is finite, each outcome is assigned a particular probability. In contrast, in a
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Algebra and Trigonometry: Functions and Applications, Teacher's Edition
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Probability, Statistics and Random Processes for Electrical Engineering
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For the experiment where we flip a coin twice, the four possible
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of outcomes that satisfy some condition, which are called "
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An event containing exactly one outcome is called an
667:"Listing All Possible Outcomes (The Sample Space)" 501: 669:. Bowling Green State University. Archived from 752:(2nd ed.). New York: Springer. p. 9. 537:Up or down? Flipping a brass tack leads to two 779:(Classics ed.). Upper Saddle River, NJ: 324: 8: 439:(most notably when the outcome must be some 625: – Observed value of a random variable 413:." The collection of all such events is a 331: 317: 18: 644:"Outcome - Probability - Math Dictionary" 494: 16:Possible result of an experiment or trial 635: 29: 474:and can have non-zero probabilities. 7: 581:or shaved dice, and other methods). 698:. Upper Saddle River, NJ: Pearson. 569:, spinning tops or wheels, drawing 725:. Dover Publications. p. 18. 14: 749:Foundations of Modern Probability 811: 37: 834:Experiment (probability theory) 665:Albert, Jim (21 January 1998). 529:that are almost equally likely. 459:probability distribution whose 722:Concepts of probability theory 104:Collectively exhaustive events 1: 692:Leon-Garcia, Alberto (2008). 525:Flipping a coin leads to two 509:and not necessarily the full 619: – Mathematical concept 541:that are not equally likely. 358:is a possible result of an 850: 773:Foerster, Paul A. (2006). 719:Pfeiffer, Paul E. (1978). 599:Event (probability theory) 401:Event (probability theory) 398: 342: 746:Kallenberg, Olav (2002). 623:Realization (probability) 451:Probability of an outcome 611:Probability distribution 395:Sets of outcomes: events 274:Law of total probability 269:Conditional independence 158:Exponential distribution 143:Probability distribution 517:Equally likely outcomes 443:). So, when defining a 253:Conditional probability 542: 530: 503: 195:Continuous or discrete 148:Bernoulli distribution 818:Outcome (probability) 557:tools used in common 536: 524: 504: 153:Binomial distribution 820:at Wikimedia Commons 646:. HighPointsLearning 493: 437:uncountably infinite 343:For other uses, see 279:Law of large numbers 248:Marginal probability 173:Poisson distribution 22:Part of a series on 238:Complementary event 180:Probability measure 168:Pareto distribution 163:Normal distribution 673:on 16 October 2000 543: 531: 499: 364:mutually exclusive 352:probability theory 289:Boole's inequality 225:Stochastic process 114:Mutual exclusivity 31:Probability theory 816:Media related to 732:978-0-486-63677-1 617:Probability space 502:{\displaystyle S} 483:probability space 479:measure-theoretic 445:probability space 377:that make up our 341: 340: 243:Joint probability 190:Bernoulli process 89:Probability space 841: 815: 799: 798: 770: 764: 763: 743: 737: 736: 716: 710: 709: 689: 683: 682: 680: 678: 662: 656: 655: 653: 651: 640: 508: 506: 505: 500: 481:definition of a 422:elementary event 333: 326: 319: 109:Elementary event 41: 19: 849: 848: 844: 843: 842: 840: 839: 838: 824: 823: 808: 803: 802: 795: 772: 771: 767: 760: 745: 744: 740: 733: 718: 717: 713: 706: 691: 690: 686: 676: 674: 664: 663: 659: 649: 647: 642: 641: 637: 632: 595: 559:games of chance 519: 491: 490: 453: 403: 397: 348: 337: 185:Random variable 136:Bernoulli trial 17: 12: 11: 5: 847: 845: 837: 836: 826: 825: 822: 821: 807: 806:External links 804: 801: 800: 793: 765: 758: 738: 731: 711: 704: 684: 657: 634: 633: 631: 628: 627: 626: 620: 614: 608: 602: 594: 591: 561:(e.g. rolling 518: 515: 498: 452: 449: 399:Main article: 396: 393: 390: 339: 338: 336: 335: 328: 321: 313: 310: 309: 308: 307: 302: 294: 293: 292: 291: 286: 284:Bayes' theorem 281: 276: 271: 266: 258: 257: 256: 255: 250: 245: 240: 232: 231: 230: 229: 228: 227: 222: 217: 215:Observed value 212: 207: 202: 200:Expected value 197: 192: 182: 177: 176: 175: 170: 165: 160: 155: 150: 140: 139: 138: 128: 127: 126: 121: 116: 111: 106: 96: 91: 83: 82: 81: 80: 75: 70: 69: 68: 58: 57: 56: 43: 42: 34: 33: 27: 26: 15: 13: 10: 9: 6: 4: 3: 2: 846: 835: 832: 831: 829: 819: 814: 810: 809: 805: 796: 794:0-13-165711-9 790: 786: 782: 781:Prentice Hall 778: 777: 769: 766: 761: 759:0-387-94957-7 755: 751: 750: 742: 739: 734: 728: 724: 723: 715: 712: 707: 705:9780131471221 701: 697: 696: 688: 685: 672: 668: 661: 658: 645: 639: 636: 629: 624: 621: 618: 615: 612: 609: 606: 603: 600: 597: 596: 592: 590: 588: 582: 580: 576: 572: 568: 564: 560: 556: 555:randomization 552: 548: 547:sample spaces 540: 535: 528: 523: 516: 514: 512: 496: 488: 484: 480: 475: 473: 468: 466: 462: 458: 450: 448: 446: 442: 438: 434: 429: 427: 423: 418: 416: 415:sigma-algebra 412: 408: 402: 394: 392: 389: 386: 384: 380: 376: 371: 369: 365: 361: 357: 353: 346: 334: 329: 327: 322: 320: 315: 314: 312: 311: 306: 303: 301: 298: 297: 296: 295: 290: 287: 285: 282: 280: 277: 275: 272: 270: 267: 265: 262: 261: 260: 259: 254: 251: 249: 246: 244: 241: 239: 236: 235: 234: 233: 226: 223: 221: 218: 216: 213: 211: 208: 206: 203: 201: 198: 196: 193: 191: 188: 187: 186: 183: 181: 178: 174: 171: 169: 166: 164: 161: 159: 156: 154: 151: 149: 146: 145: 144: 141: 137: 134: 133: 132: 129: 125: 122: 120: 117: 115: 112: 110: 107: 105: 102: 101: 100: 97: 95: 92: 90: 87: 86: 85: 84: 79: 76: 74: 73:Indeterminism 71: 67: 64: 63: 62: 59: 55: 52: 51: 50: 47: 46: 45: 44: 40: 36: 35: 32: 28: 25: 21: 20: 775: 768: 748: 741: 721: 714: 694: 687: 675:. 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Retrieved 638: 605:Sample space 583: 575:marked cards 565:, shuffling 544: 538: 526: 476: 471: 469: 461:sample space 454: 430: 426:sample space 419: 404: 385:, which are 379:sample space 378: 374: 372: 368:sample space 355: 349: 305:Tree diagram 300:Venn diagram 264:Independence 210:Markov chain 118: 94:Sample space 551:probability 441:real number 220:Random walk 61:Determinism 49:Probability 783:. p.  630:References 587:thumb tack 477:Under the 465:continuous 360:experiment 131:Experiment 78:Randomness 24:statistics 511:power set 487:σ-algebra 433:power set 124:Singleton 828:Category 677:June 25, 593:See also 545:In some 539:outcomes 527:outcomes 457:discrete 375:outcomes 205:Variance 650:25 June 356:outcome 345:Outcome 119:Outcome 791:  756:  729:  702:  579:loaded 411:events 383:events 66:System 54:Axioms 567:cards 472:atoms 354:, an 99:Event 789:ISBN 754:ISBN 727:ISBN 700:ISBN 679:2013 652:2013 571:lots 563:dice 407:sets 388:sets 785:633 489:on 350:In 830:: 787:. 577:, 513:. 417:. 370:. 797:. 762:. 735:. 708:. 681:. 654:. 497:S 347:. 332:e 325:t 318:v

Index

statistics
Probability theory

Probability
Axioms
Determinism
System
Indeterminism
Randomness
Probability space
Sample space
Event
Collectively exhaustive events
Elementary event
Mutual exclusivity
Outcome
Singleton
Experiment
Bernoulli trial
Probability distribution
Bernoulli distribution
Binomial distribution
Exponential distribution
Normal distribution
Pareto distribution
Poisson distribution
Probability measure
Random variable
Bernoulli process
Continuous or discrete

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