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Workshop2Q8

R Software Module: rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Sun, 21 Oct 2007 09:15:08 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Oct/21/7afc5evunhgwhsy1192983065.htm/, Retrieved Sun, 21 Oct 2007 18:11:05 +0200

User-defined keywords:

totale werkloosheid

Dataseries X:

» Textbox « » Textfile « » CSV «

580 574 563 556 546 545 605 628 631 626 614 606 602 589 574 558 552 546 607 636 631 623 618 605 619 596 570 546 528 506 555 568 564 553 541 542 540 521 505 491 482 478 523 531 532 540 525 533 531 508 495 482 470 466 515 518 516 511 500 498 494 476 458 443 430 424 476 481 470 460 451 450 444 429 421 400 389 384 432 446 431 423 416 416 413 399 386 374 365 365 418 428 424 421 417 423 423 419 406 398 390 391 444 460 455 456 452 459 461 451 443 439 430 436 488 506 502 501 501 515 521 520 512 509 505 511 570 592 594 586 586 592 594 586 572 563 555 554 601 622 617 606 595 599 600 592 575 567 555 555 608 631 629 624 610 616 621 604 584 574 555 545 599 620 608 590 579 580 579 572 560 551 537 541 588 607 599 578 563 566 561 554 540 526 512 505 554 584 569 540 522 526 527 516 503 489 479 475 524 552 532 511 492 492 493 481 462 457 442 439 488 521 501 485 464 460 467 460 448 443 436 431 484 510 513 503 471 471 476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 557 561 549 532 526 511 499 555 565 542

Text written by user:

Output produced by software:

Summary of compuational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 4 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 526.215488215488 3.77048837568314 139.561625918061 Geometric Mean 522.039579959443 Harmonic Mean 517.687921992188 Quadratic Mean 530.198876351929 Winsorized Mean ( 1 / 99 ) 526.198653198653 3.76886959289520 139.617102748953 Winsorized Mean ( 2 / 99 ) 526.259259259259 3.76034538792565 139.949713382462 Winsorized Mean ( 3 / 99 ) 526.360269360269 3.74695321852479 140.476872451453 Winsorized Mean ( 4 / 99 ) 526.360269360269 3.74099831291371 140.700482954858 Winsorized Mean ( 5 / 99 ) 526.410774410774 3.73465843759307 140.952856387595 Winsorized Mean ( 6 / 99 ) 526.410774410774 3.7302882077477 141.117990110639 Winsorized Mean ( 7 / 99 ) 526.434343434343 3.72738573583517 141.234200252792 Winsorized Mean ( 8 / 99 ) 526.569023569024 3.69981792619166 142.322955905843 Winsorized Mean ( 9 / 99 ) 526.599326599327 3.69627209846562 142.467684350924 Winsorized Mean ( 10 / 99 ) 526.565656565657 3.68629029229104 142.844327172724 Winsorized Mean ( 11 / 99 ) 526.750841750842 3.65770808018794 144.011175906574 Winsorized Mean ( 12 / 99 ) 526.993265993266 3.62331667470911 145.444992338566 Winsorized Mean ( 13 / 99 ) 527.080808080808 3.60563970607597 146.182328531774 Winsorized Mean ( 14 / 99 ) 527.080808080808 3.60563970607597 146.182328531774 Winsorized Mean ( 15 / 99 ) 527.080808080808 3.59597311174827 146.575291778129 Winsorized Mean ( 16 / 99 ) 527.13468013468 3.59042133483858 146.816941794487 Winsorized Mean ( 17 / 99 ) 527.191919191919 3.58456410020713 147.072811213351 Winsorized Mean ( 18 / 99 ) 527.252525252525 3.56700110917993 147.813950462646 Winsorized Mean ( 19 / 99 ) 527.188552188552 3.56146617649209 148.02570797059 Winsorized Mean ( 20 / 99 ) 527.255892255892 3.5422044800318 148.849648637777 Winsorized Mean ( 21 / 99 ) 527.185185185185 3.53617862573114 149.083301773587 Winsorized Mean ( 22 / 99 ) 527.037037037037 3.52371712930013 149.568486259768 Winsorized Mean ( 23 / 99 ) 527.037037037037 3.50958185656148 150.170891740762 Winsorized Mean ( 24 / 99 ) 526.956228956229 3.50292448146357 150.433225650374 Winsorized Mean ( 25 / 99 ) 527.208754208754 3.46301956659196 152.239611723474 Winsorized Mean ( 26 / 99 ) 527.296296296296 3.45457556604277 152.637071100551 Winsorized Mean ( 27 / 99 ) 527.296296296296 3.43844630324808 153.353069902006 Winsorized Mean ( 28 / 99 ) 527.107744107744 3.42325901004394 153.978341271050 Winsorized Mean ( 29 / 99 ) 527.205387205387 3.41393219277798 154.427609406146 Winsorized Mean ( 30 / 99 ) 527.104377104377 3.40589157477466 154.762524153239 Winsorized Mean ( 31 / 99 ) 527.208754208754 3.39597343316019 155.245252822296 Winsorized Mean ( 32 / 99 ) 527.531986531986 3.3471083550342 157.608278721708 Winsorized Mean ( 33 / 99 ) 527.531986531986 3.3471083550342 157.608278721708 Winsorized Mean ( 34 / 99 ) 527.760942760943 3.30661904218294 159.607422575214 Winsorized Mean ( 35 / 99 ) 527.760942760943 3.30661904218294 159.607422575214 Winsorized Mean ( 36 / 99 ) 528.003367003367 3.26439599971903 161.746113844280 Winsorized Mean ( 37 / 99 ) 527.878787878788 3.23388300988698 163.233730553919 Winsorized Mean ( 38 / 99 ) 527.750841750842 3.22401898495375 163.693465892668 Winsorized Mean ( 39 / 99 ) 527.619528619529 3.21398403952053 164.163705274106 Winsorized Mean ( 40 / 99 ) 527.619528619529 3.19182287483698 165.303511287880 Winsorized Mean ( 41 / 99 ) 527.619528619529 3.19182287483698 165.303511287880 Winsorized Mean ( 42 / 99 ) 527.902356902357 3.1669507328912 166.691054401222 Winsorized Mean ( 43 / 99 ) 527.902356902357 3.11995915824684 169.201688267931 Winsorized Mean ( 44 / 99 ) 528.050505050505 3.08341401939762 171.255141777446 Winsorized Mean ( 45 / 99 ) 528.050505050505 3.0592479658527 172.607945137040 Winsorized Mean ( 46 / 99 ) 528.050505050505 3.0592479658527 172.607945137040 Winsorized Mean ( 47 / 99 ) 528.208754208754 3.04582694898382 173.420474326350 Winsorized Mean ( 48 / 99 ) 528.531986531986 2.99325451587031 176.574355347899 Winsorized Mean ( 49 / 99 ) 528.531986531986 2.99325451587031 176.574355347899 Winsorized Mean ( 50 / 99 ) 528.700336700337 2.97932926675953 177.456161894915 Winsorized Mean ( 51 / 99 ) 528.700336700337 2.97932926675953 177.456161894915 Winsorized Mean ( 52 / 99 ) 528.700336700337 2.95200469472843 179.098745216926 Winsorized Mean ( 53 / 99 ) 528.700336700337 2.92430424287937 180.795256850484 Winsorized Mean ( 54 / 99 ) 528.882154882155 2.90950209195919 181.777547554887 Winsorized Mean ( 55 / 99 ) 529.06734006734 2.89452449607992 182.782125625076 Winsorized Mean ( 56 / 99 ) 528.878787878788 2.88073127213370 183.591851483967 Winsorized Mean ( 57 / 99 ) 528.686868686869 2.866806732201 184.41664125749 Winsorized Mean ( 58 / 99 ) 528.686868686869 2.866806732201 184.41664125749 Winsorized Mean ( 59 / 99 ) 528.686868686869 2.83644679425554 186.390546707092 Winsorized Mean ( 60 / 99 ) 528.686868686869 2.83644679425554 186.390546707092 Winsorized Mean ( 61 / 99 ) 528.686868686869 2.80520694252636 188.466262745926 Winsorized Mean ( 62 / 99 ) 529.104377104377 2.77187558384532 190.883162356938 Winsorized Mean ( 63 / 99 ) 529.104377104377 2.70805851166559 195.381442027614 Winsorized Mean ( 64 / 99 ) 529.319865319865 2.69114696046327 196.689319868561 Winsorized Mean ( 65 / 99 ) 529.976430976431 2.64026574785943 200.728442357026 Winsorized Mean ( 66 / 99 ) 529.531986531986 2.60865864809970 202.990140897787 Winsorized Mean ( 67 / 99 ) 529.531986531986 2.60865864809970 202.990140897787 Winsorized Mean ( 68 / 99 ) 529.760942760943 2.59106161061399 204.457099974326 Winsorized Mean ( 69 / 99 ) 528.83164983165 2.52639533397193 209.322603917351 Winsorized Mean ( 70 / 99 ) 529.774410774411 2.45438846188499 215.847824825390 Winsorized Mean ( 71 / 99 ) 529.774410774411 2.45438846188499 215.847824825390 Winsorized Mean ( 72 / 99 ) 530.016835016835 2.43616965797356 217.56154514202 Winsorized Mean ( 73 / 99 ) 529.771043771044 2.41920219388462 218.985847942030 Winsorized Mean ( 74 / 99 ) 529.771043771044 2.41920219388462 218.985847942030 Winsorized Mean ( 75 / 99 ) 530.023569023569 2.36412744737146 224.194160772877 Winsorized Mean ( 76 / 99 ) 530.279461279461 2.34516375300587 226.116176578197 Winsorized Mean ( 77 / 99 ) 530.020202020202 2.25399888015125 235.14661284332 Winsorized Mean ( 78 / 99 ) 529.757575757576 2.23636948107729 236.882849743766 Winsorized Mean ( 79 / 99 ) 530.023569023569 2.21683973545561 239.089709800170 Winsorized Mean ( 80 / 99 ) 530.023569023569 2.21683973545561 239.089709800170 Winsorized Mean ( 81 / 99 ) 530.569023569024 2.17716966228731 243.696682330037 Winsorized Mean ( 82 / 99 ) 530.569023569024 2.13870008938948 248.080142793879 Winsorized Mean ( 83 / 99 ) 531.407407407407 2.07894761878524 255.613658855876 Winsorized Mean ( 84 / 99 ) 531.407407407407 2.07894761878524 255.613658855876 Winsorized Mean ( 85 / 99 ) 531.407407407407 2.03950681274118 260.556818975846 Winsorized Mean ( 86 / 99 ) 531.986531986532 1.99910670891602 266.112123787026 Winsorized Mean ( 87 / 99 ) 531.693602693603 1.93947666318983 274.142820475671 Winsorized Mean ( 88 / 99 ) 531.693602693603 1.93947666318983 274.142820475671 Winsorized Mean ( 89 / 99 ) 531.693602693603 1.89885855743708 280.006955026307 Winsorized Mean ( 90 / 99 ) 531.996632996633 1.87807138145824 283.267525531198 Winsorized Mean ( 91 / 99 ) 532.30303030303 1.85720420846356 286.61524019666 Winsorized Mean ( 92 / 99 ) 532.922558922559 1.77407525539959 300.394561786796 Winsorized Mean ( 93 / 99 ) 532.922558922559 1.73244224025918 307.613464124976 Winsorized Mean ( 94 / 99 ) 533.239057239057 1.71159092248726 311.545854931365 Winsorized Mean ( 95 / 99 ) 533.239057239057 1.66940134278673 319.419329296166 Winsorized Mean ( 96 / 99 ) 533.239057239057 1.66940134278673 319.419329296166 Winsorized Mean ( 97 / 99 ) 532.912457912458 1.64783147644903 323.402280833262 Winsorized Mean ( 98 / 99 ) 532.912457912458 1.64783147644903 323.402280833262 Winsorized Mean ( 99 / 99 ) 532.912457912458 1.60419970168439 332.198327523005 Trimmed Mean ( 1 / 99 ) 526.389830508475 3.73785927318998 140.826551251952 Trimmed Mean ( 2 / 99 ) 526.58361774744 3.70551394843088 142.108119163989 Trimmed Mean ( 3 / 99 ) 526.749140893471 3.67632659916373 143.281377942127 Trimmed Mean ( 4 / 99 ) 526.882352941176 3.6507466069502 144.321808568722 Trimmed Mean ( 5 / 99 ) 527.017421602787 3.62570928289203 145.355675395578 Trimmed Mean ( 6 / 99 ) 527.143859649123 3.60102033311609 146.387359938334 Trimmed Mean ( 7 / 99 ) 527.272084805654 3.57608899759674 147.443781505438 Trimmed Mean ( 8 / 99 ) 527.398576512456 3.55054890861945 148.540011723855 Trimmed Mean ( 9 / 99 ) 527.508960573477 3.52800779675040 149.520350000178 Trimmed Mean ( 10 / 99 ) 527.617328519856 3.50494160650831 150.535269272426 Trimmed Mean ( 11 / 99 ) 527.730909090909 3.48206912698173 151.556700871228 Trimmed Mean ( 12 / 99 ) 527.827838827839 3.46144715600627 152.487620072997 Trimmed Mean ( 13 / 99 ) 527.90405904059 3.44354795076299 153.302369122992 Trimmed Mean ( 14 / 99 ) 527.973977695167 3.42657224514762 154.082254778907 Trimmed Mean ( 15 / 99 ) 528.044943820225 3.40879521736241 154.906619538385 Trimmed Mean ( 16 / 99 ) 528.116981132075 3.3910372178971 155.739069552170 Trimmed Mean ( 17 / 99 ) 528.186311787072 3.3729083969944 156.596696268935 Trimmed Mean ( 18 / 99 ) 528.252873563218 3.35439260590732 157.480931907889 Trimmed Mean ( 19 / 99 ) 528.316602316602 3.33636547302651 158.350938045571 Trimmed Mean ( 20 / 99 ) 528.385214007782 3.31787305542982 159.254198451945 Trimmed Mean ( 21 / 99 ) 528.450980392157 3.29988733194077 160.142128271197 Trimmed Mean ( 22 / 99 ) 528.521739130435 3.28143087800247 161.064413294046 Trimmed Mean ( 23 / 99 ) 528.601593625498 3.26289817978957 162.003704835064 Trimmed Mean ( 24 / 99 ) 528.682730923695 3.24438071351989 162.95335769954 Trimmed Mean ( 25 / 99 ) 528.769230769231 3.22534972508621 163.941673256874 Trimmed Mean ( 26 / 99 ) 528.844897959184 3.20792267951383 164.855874281649 Trimmed Mean ( 27 / 99 ) 528.917695473251 3.19012425000886 165.798462386467 Trimmed Mean ( 28 / 99 ) 528.991701244813 3.17238141818130 166.749085785554 Trimmed Mean ( 29 / 99 ) 529.075313807531 3.15459263086442 167.715890993682 Trimmed Mean ( 30 / 99 ) 529.15611814346 3.13641670852554 168.713588569110 Trimmed Mean ( 31 / 99 ) 529.242553191489 3.11772170999826 169.752980676324 Trimmed Mean ( 32 / 99 ) 529.326180257511 3.09860044905231 170.827503887893 Trimmed Mean ( 33 / 99 ) 529.398268398268 3.08124310746219 171.813209777627 Trimmed Mean ( 34 / 99 ) 529.471615720524 3.06292402634644 172.864756411244 Trimmed Mean ( 35 / 99 ) 529.537444933921 3.04584169098252 173.855866016170 Trimmed Mean ( 36 / 99 ) 529.604444444444 3.02779385462457 174.914300600598 Trimmed Mean ( 37 / 99 ) 529.663677130045 3.01102143239642 175.908305212060 Trimmed Mean ( 38 / 99 ) 529.72850678733 2.994887012725 176.877626613813 Trimmed Mean ( 39 / 99 ) 529.799086757991 2.97830944856437 177.885842927896 Trimmed Mean ( 40 / 99 ) 529.875576036866 2.96126080445350 178.935801682843 Trimmed Mean ( 41 / 99 ) 529.953488372093 2.94434920454248 179.990025488312 Trimmed Mean ( 42 / 99 ) 530.032863849765 2.92641911275192 181.119943326005 Trimmed Mean ( 43 / 99 ) 530.104265402844 2.90872859033161 182.246039443098 Trimmed Mean ( 44 / 99 ) 530.177033492823 2.89236287736717 183.302391840759 Trimmed Mean ( 45 / 99 ) 530.246376811594 2.87684145427372 184.315467237126 Trimmed Mean ( 46 / 99 ) 530.317073170732 2.86154432460200 185.325479186659 Trimmed Mean ( 47 / 99 ) 530.389162561576 2.84525999982528 186.411492304445 Trimmed Mean ( 48 / 99 ) 530.457711442786 2.82862012378090 187.532326091827 Trimmed Mean ( 49 / 99 ) 530.517587939699 2.81356330679647 188.557188906386 Trimmed Mean ( 50 / 99 ) 530.578680203046 2.79750128281479 189.661639643356 Trimmed Mean ( 51 / 99 ) 530.635897435897 2.78108271370697 190.801911363722 Trimmed Mean ( 52 / 99 ) 530.694300518135 2.76356250780135 192.032674860807 Trimmed Mean ( 53 / 99 ) 530.753926701571 2.74624137316134 193.265578142023 Trimmed Mean ( 54 / 99 ) 530.814814814815 2.72913429471827 194.49933843201 Trimmed Mean ( 55 / 99 ) 530.871657754011 2.71161439345109 195.776972948712 Trimmed Mean ( 56 / 99 ) 530.924324324324 2.69365654126423 197.101715155988 Trimmed Mean ( 57 / 99 ) 530.924324324324 2.67512180497651 198.467345799601 Trimmed Mean ( 58 / 99 ) 531.049723756906 2.65596698101492 199.945905786064 Trimmed Mean ( 59 / 99 ) 531.117318435754 2.63544960806445 201.528163092377 Trimmed Mean ( 60 / 99 ) 531.186440677966 2.61505193908649 203.126535553066 Trimmed Mean ( 61 / 99 ) 531.257142857143 2.59317931023334 204.867106860165 Trimmed Mean ( 62 / 99 ) 531.329479768786 2.57137799596457 206.632195111973 Trimmed Mean ( 63 / 99 ) 531.391812865497 2.54981837335872 208.403790018003 Trimmed Mean ( 64 / 99 ) 531.455621301775 2.53005265276148 210.057138819505 Trimmed Mean ( 65 / 99 ) 531.51497005988 2.50971499991758 211.782999295672 Trimmed Mean ( 66 / 99 ) 531.557575757576 2.49062323588202 213.423519101368 Trimmed Mean ( 67 / 99 ) 531.613496932515 2.47167281186899 215.082471425709 Trimmed Mean ( 68 / 99 ) 531.670807453416 2.45121304102233 216.901101028604 Trimmed Mean ( 69 / 99 ) 531.723270440252 2.43012224888985 218.805152984859 Trimmed Mean ( 70 / 99 ) 531.802547770701 2.41073595472707 220.597592501958 Trimmed Mean ( 71 / 99 ) 531.858064516129 2.39386239904502 222.175704304601 Trimmed Mean ( 72 / 99 ) 531.915032679739 2.37553875106114 223.913431192034 Trimmed Mean ( 73 / 99 ) 531.966887417219 2.3566994771244 225.725381017318 Trimmed Mean ( 74 / 99 ) 532.026845637584 2.33714914507243 227.639235929505 Trimmed Mean ( 75 / 99 ) 532.08843537415 2.31588706184948 229.755778742173 Trimmed Mean ( 76 / 99 ) 532.144827586207 2.29602728930895 231.767640595582 Trimmed Mean ( 77 / 99 ) 532.195804195804 2.27554409535355 233.876287118539 Trimmed Mean ( 78 / 99 ) 532.255319148936 2.25852890441745 235.664603675384 Trimmed Mean ( 79 / 99 ) 532.323741007194 2.24087058361465 237.552201764605 Trimmed Mean ( 80 / 99 ) 532.386861313869 2.2227368393533 239.518620417865 Trimmed Mean ( 81 / 99 ) 532.451851851852 2.20283546404387 241.712039116349 Trimmed Mean ( 82 / 99 ) 532.503759398496 2.18357818211128 243.867503238938 Trimmed Mean ( 83 / 99 ) 532.557251908397 2.16482205456529 246.005093483463 Trimmed Mean ( 84 / 99 ) 532.589147286822 2.14806261871982 247.939302441857 Trimmed Mean ( 85 / 99 ) 532.589147286822 2.12953616456677 250.09631493869 Trimmed Mean ( 86 / 99 ) 532.656 2.11162997736117 252.248739462224 Trimmed Mean ( 87 / 99 ) 532.674796747967 2.09451139890139 254.319359172438 Trimmed Mean ( 88 / 99 ) 532.702479338843 2.07940327807069 256.180455689718 Trimmed Mean ( 89 / 99 ) 532.731092436975 2.06253527733696 258.289445174877 Trimmed Mean ( 90 / 99 ) 532.760683760684 2.04649209881189 260.328727420928 Trimmed Mean ( 91 / 99 ) 532.782608695652 2.03001063783724 262.453111705501 Trimmed Mean ( 92 / 99 ) 532.796460176991 2.01304058047528 264.672488644615 Trimmed Mean ( 93 / 99 ) 532.792792792793 1.99992289438252 266.406667121681 Trimmed Mean ( 94 / 99 ) 532.788990825688 1.98798948028316 268.003928647449 Trimmed Mean ( 95 / 99 ) 532.775700934579 1.97584194809371 269.644898190668 Trimmed Mean ( 96 / 99 ) 532.761904761905 1.96501096612268 271.124138209335 Trimmed Mean ( 97 / 99 ) 532.747572815534 1.95249689783029 272.854504100646 Trimmed Mean ( 98 / 99 ) 532.742574257426 1.93976896987870 274.642280874686 Trimmed Mean ( 99 / 99 ) 532.737373737374 1.92508561351815 276.734380017407 Median 532 Midrange 500.5 Midmean - Weighted Average at Xnp 530.966666666667 Midmean - Weighted Average at X(n+1)p 531.598684210526 Midmean - Empirical Distribution Function 531.598684210526 Midmean - Empirical Distribution Function - Averaging 531.598684210526 Midmean - Empirical Distribution Function - Interpolation 531.598684210526 Midmean - Closest Observation 531.598684210526 Midmean - True Basic - Statistics Graphics Toolkit 531.598684210526 Midmean - MS Excel (old versions) 531.598684210526 Number of observations 297

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/21/7afc5evunhgwhsy1192983065/1c4xs1192983300.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/21/7afc5evunhgwhsy1192983065/1c4xs1192983300.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/21/7afc5evunhgwhsy1192983065/22saa1192983300.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Oct/21/7afc5evunhgwhsy1192983065/22saa1192983300.ps (open in new window)

Parameters:

R code (references can be found in the software module):

geomean <- function(x) { return(exp(mean(log(x)))) } harmean <- function(x) { return(1/mean(1/x)) } quamean <- function(x) { return(sqrt(mean(x*x))) } winmean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) win <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn } return(win) } trimean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) tri <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { tri[j,1] <- mean(x,trim=j/n) tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2) } return(tri) } midrange <- function(x) { return((max(x)+min(x))/2) } q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } midmean <- function(x,def) { x <-sort(x[!is.na(x)]) n<-length(x) if (def==1) { qvalue1 <- q1(x,n,0.25,i,f) qvalue3 <- q1(x,n,0.75,i,f) } if (def==2) { qvalue1 <- q2(x,n,0.25,i,f) qvalue3 <- q2(x,n,0.75,i,f) } if (def==3) { qvalue1 <- q3(x,n,0.25,i,f) qvalue3 <- q3(x,n,0.75,i,f) } if (def==4) { qvalue1 <- q4(x,n,0.25,i,f) qvalue3 <- q4(x,n,0.75,i,f) } if (def==5) { qvalue1 <- q5(x,n,0.25,i,f) qvalue3 <- q5(x,n,0.75,i,f) } if (def==6) { qvalue1 <- q6(x,n,0.25,i,f) qvalue3 <- q6(x,n,0.75,i,f) } if (def==7) { qvalue1 <- q7(x,n,0.25,i,f) qvalue3 <- q7(x,n,0.75,i,f) } if (def==8) { qvalue1 <- q8(x,n,0.25,i,f) qvalue3 <- q8(x,n,0.75,i,f) } midm <- 0 myn <- 0 roundno4 <- round(n/4) round3no4 <- round(3*n/4) for (i in 1:n) { if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){ midm = midm + x[i] myn = myn + 1 } } midm = midm / myn return(midm) } (arm <- mean(x)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') lb <- win[,1] - 2*win[,2] ub <- win[,1] + 2*win[,2] if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() bitmap(file='test2.png') lb <- tri[,1] - 2*tri[,2] ub <- tri[,1] + 2*tri[,2] if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Measure',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.element(a,'S.E.',header=TRUE) a<-table.element(a,'Value/S.E.',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE) a<-table.element(a,arm) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean')) a<-table.element(a,armose) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE) a<-table.element(a,geo) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE) a<-table.element(a,har) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE) a<-table.element(a,qua) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) for (j in 1:length(win[,1])) { a<-table.row.start(a) mylabel <- paste('Winsorized Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(win[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE) a<-table.element(a,win[j,1]) a<-table.element(a,win[j,2]) a<-table.element(a,win[j,1]/win[j,2]) a<-table.row.end(a) } for (j in 1:length(tri[,1])) { a<-table.row.start(a) mylabel <- paste('Trimmed Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(tri[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE) a<-table.element(a,tri[j,1]) a<-table.element(a,tri[j,2]) a<-table.element(a,tri[j,1]/tri[j,2]) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE) a<-table.element(a,median(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE) a<-table.element(a,midr) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[1]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[2]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[3]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[4]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[5]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[6]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[7]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[8]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of observations',header=TRUE) a<-table.element(a,length(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

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Software written by Ed van Stee & Patrick Wessa

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