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Ranking (statistics)

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is another approach. Alternatively, intersection/overlap-based approaches offer additional flexibility. One example is the "Rank–rank hypergeometric overlap" approach, which is designed to compare ranking of the genes that are at the "top" of two ordered lists of differentially expressed genes. A
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similar approach is taken by the "Rank Biased Overlap (RBO)", which also implements an adjustable probability, p, to customize the weight assigned at a desired depth of ranking. These approaches have the advantages of addressing
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As another example, the ordinal data hot, cold, warm would be replaced by 3, 1, 2. In these examples, the ranks are assigned to values in ascending order, although descending ranks can also be used.
596: 316: 522: 437: 157:, i.e. the largest number will have a rank 1. This is generally uncommon for statistics where the ranking is usually in ascending order, where the smallest number has a rank 1. 182:, sets of different sizes, and top-weightedness (taking into account the absolute ranking position, which may be ignored in standard non-weighted rank correlation approaches). 234: 372: 457: 339: 439:. In the presence of ties, we may either use a midrank (corresponding to the "fractional rank" mentioned above), defined as the average of all indices 80: 122:
Some ranks can have non-integer values for tied data values. For example, when there is an even number of copies of the same data value, the
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For example, if the numerical data 3.4, 5.1, 2.6, 7.3 are observed, the ranks of these data items would be 2, 3, 1 and 4 respectively.
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The distribution of values in decreasing order of rank is often of interest when values vary widely in scale; this is the
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Webber, William; Moffat, Alistair; Zobel, Justin (November 2010). "A Similarity Measure for Indefinite Rankings".
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is useful to measure the statistical dependence between the rankings of athletes in two tournaments. And the
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Plaisier, Seema B.; Taschereau, Richard; Wong, Justin A.; Graeber, Thomas G. (September 2010).
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be a set of random variables. By sorting them into order, we have defined their
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function which assigns fractional ranks ("1 2.5 2.5 4"). The functions have the
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can be used to compare two rankings for the same set of objects. For example,
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values are replaced by their rank when the data are sorted.
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If all the values are unique, the rank of variable number
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function which assigns competition ranks ("1224") and the
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employ calculations based on ranks. Examples include:
534: 465: 445: 380: 347: 327: 248: 196: 591:{\displaystyle \sum _{j=1}^{n}1\{X_{j}\leq X_{i}\}} 590: 516: 451: 431: 366: 333: 310: 228: 689: 748: 311:{\displaystyle X_{n,(1)}\leq ...\leq X_{n,(n)}} 729:. Cambridge, UK: Cambridge University Press. 585: 559: 16:Data transformation of statistics into rank 608: 666: 160: 55:Ranks are related to the indexed list of 718: 153:argument, which is by default is set to 130:is another type of statistical ranking. 692:ACM Transactions on Information Systems 171:Spearman's rank correlation coefficient 91:Spearman's rank correlation coefficient 749: 524:, or the uprank (corresponding to the 724: 517:{\displaystyle X_{j}=X_{N,(R_{n,j})}} 432:{\displaystyle X_{i}=X_{N,(R_{n,i})}} 175:Kendall rank correlation coefficient 141:provides two ranking functions, the 13: 62: 14: 768: 683: 634: 526:"modified competition ranking" 509: 490: 424: 405: 303: 297: 266: 260: 133: 1: 725:Vaart, A. W. van der (1998). 601: 229:{\displaystyle X_{1},..X_{n}} 185: 126:of the tied data ends in ½. 7: 124:fractional statistical rank 10: 773: 18: 101:Wilcoxon signed-rank test 757:Nonparametric statistics 704:10.1145/1852102.1852106 367:{\displaystyle R_{n,i}} 341:is the unique solution 647:Nucleic Acids Research 592: 555: 518: 453: 433: 368: 335: 312: 230: 161:Comparison of rankings 113:rank-size distribution 727:Asymptotic statistics 616:"Excel RANK.AVG Help" 593: 535: 519: 454: 434: 369: 336: 313: 231: 532: 463: 443: 378: 345: 325: 246: 194: 106:Van der Waerden test 19:For other uses, see 96:Mann–Whitney U test 81:Kruskal–Wallis test 36:data transformation 659:10.1093/nar/gkq636 588: 514: 449: 429: 364: 331: 308: 226: 452:{\displaystyle i} 334:{\displaystyle i} 69:statistical tests 764: 741: 740: 722: 716: 715: 687: 681: 680: 670: 638: 632: 631: 629: 627: 612: 597: 595: 594: 589: 584: 583: 571: 570: 554: 549: 523: 521: 520: 515: 513: 512: 508: 507: 475: 474: 458: 456: 455: 450: 438: 436: 435: 430: 428: 427: 423: 422: 390: 389: 374:to the equation 373: 371: 370: 365: 363: 362: 340: 338: 337: 332: 317: 315: 314: 309: 307: 306: 270: 269: 238:order statistics 235: 233: 232: 227: 225: 224: 206: 205: 167:rank correlation 152: 148: 144: 57:order statistics 772: 771: 767: 766: 765: 763: 762: 761: 747: 746: 745: 744: 737: 723: 719: 688: 684: 639: 635: 625: 623: 614: 613: 609: 604: 579: 575: 566: 562: 550: 539: 533: 530: 529: 497: 493: 483: 479: 470: 466: 464: 461: 460: 444: 441: 440: 412: 408: 398: 394: 385: 381: 379: 376: 375: 352: 348: 346: 343: 342: 326: 323: 322: 290: 286: 253: 249: 247: 244: 243: 220: 216: 201: 197: 195: 192: 191: 188: 163: 150: 146: 142: 139:Microsoft Excel 136: 128:Percentile rank 65: 63:Use for testing 24: 17: 12: 11: 5: 770: 760: 759: 743: 742: 735: 717: 682: 633: 620:Office Support 606: 605: 603: 600: 587: 582: 578: 574: 569: 565: 561: 558: 553: 548: 545: 542: 538: 511: 506: 503: 500: 496: 492: 489: 486: 482: 478: 473: 469: 448: 426: 421: 418: 415: 411: 407: 404: 401: 397: 393: 388: 384: 361: 358: 355: 351: 330: 319: 318: 305: 302: 299: 296: 293: 289: 285: 282: 279: 276: 273: 268: 265: 262: 259: 256: 252: 223: 219: 215: 212: 209: 204: 200: 187: 184: 162: 159: 135: 132: 109: 108: 103: 98: 93: 88: 83: 78: 67:Some kinds of 64: 61: 15: 9: 6: 4: 3: 2: 769: 758: 755: 754: 752: 738: 736:9780521784504 732: 728: 721: 713: 709: 705: 701: 697: 693: 686: 678: 674: 669: 664: 660: 656: 652: 648: 644: 637: 621: 617: 611: 607: 599: 580: 576: 572: 567: 563: 556: 551: 546: 543: 540: 536: 528:) defined by 527: 504: 501: 498: 494: 487: 484: 480: 476: 471: 467: 446: 419: 416: 413: 409: 402: 399: 395: 391: 386: 382: 359: 356: 353: 349: 328: 300: 294: 291: 287: 283: 280: 277: 274: 271: 263: 257: 254: 250: 242: 241: 240: 239: 221: 217: 213: 210: 207: 202: 198: 183: 181: 180:disjoint sets 176: 172: 168: 158: 156: 140: 131: 129: 125: 120: 118: 114: 107: 104: 102: 99: 97: 94: 92: 89: 87: 86:Rank products 84: 82: 79: 77: 76:Friedman test 74: 73: 72: 70: 60: 58: 53: 50: 47: 45: 41: 37: 33: 29: 22: 726: 720: 695: 691: 685: 653:(17): e169. 650: 646: 636: 624:. Retrieved 619: 610: 320: 189: 164: 154: 137: 121: 110: 66: 54: 51: 48: 31: 25: 698:(4): 1–38. 622:. Microsoft 134:Computation 626:21 January 602:References 459:such that 186:Definition 155:descending 28:statistics 573:≤ 537:∑ 284:≤ 272:≤ 117:power law 40:numerical 38:in which 751:Category 712:16050561 677:20660011 147:Rank.AVG 668:2943622 143:Rank.EQ 44:ordinal 34:is the 32:ranking 21:Ranking 733:  710:  675:  665:  708:S2CID 151:order 731:ISBN 673:PMID 628:2021 190:Let 700:doi 663:PMC 655:doi 42:or 26:In 753:: 706:. 696:28 694:. 671:. 661:. 651:38 649:. 645:. 618:. 598:. 165:A 119:. 30:, 739:. 714:. 702:: 679:. 657:: 630:. 586:} 581:i 577:X 568:j 564:X 560:{ 557:1 552:n 547:1 544:= 541:j 510:) 505:j 502:, 499:n 495:R 491:( 488:, 485:N 481:X 477:= 472:j 468:X 447:i 425:) 420:i 417:, 414:n 410:R 406:( 403:, 400:N 396:X 392:= 387:i 383:X 360:i 357:, 354:n 350:R 329:i 304:) 301:n 298:( 295:, 292:n 288:X 281:. 278:. 275:. 267:) 264:1 261:( 258:, 255:n 251:X 222:n 218:X 214:. 211:. 208:, 203:1 199:X 23:.

Index

Ranking
statistics
data transformation
numerical
ordinal
order statistics
statistical tests
Friedman test
Kruskal–Wallis test
Rank products
Spearman's rank correlation coefficient
Mann–Whitney U test
Wilcoxon signed-rank test
Van der Waerden test
rank-size distribution
power law
fractional statistical rank
Percentile rank
Microsoft Excel
rank correlation
Spearman's rank correlation coefficient
Kendall rank correlation coefficient
disjoint sets
order statistics
"modified competition ranking"
"Excel RANK.AVG Help"
"Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures"
doi
10.1093/nar/gkq636
PMC

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