CaseStatistiek - EDA Fixed Location

*The author of this computation has been verified*

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

Title produced by software: Central Tendency

Date of computation: Tue, 29 Dec 2009 14:22:14 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/29/t1262122259arblnw2vn5drvw0.htm/, Retrieved Tue, 29 Dec 2009 22:31:02 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Dec/29/t1262122259arblnw2vn5drvw0.htm/}, year = {2009}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

CaseStatistiek - EDA Fixed Location

Dataseries X:

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15 14.4 13.5 12.8 12.3 12.2 14.5 17.2 18 18.1 18 18.3 18.7 18.6 18.3 17.9 17.4 17.4 20.1 23.2 24.2 24.2 23.9 23.8 23.8 23.3 22.4 21.5 20.5 19.9 22 24.9 25.7 25.3 24.4 23.8 23.5 23 22.2 21.4 20.3 19.5 21.7 24.7 25.3 24.9 24.1 23.4 23.1 22.4 21.3 20.3 19.3 18.7 21 24 24.8 24.2 23.3 22.7 22.3 21.8 21.2 20.5 19.7 19.2 21.2 23.9 24.8 24.2 23 22.2 21.8 21.2 20.5 19.7 19 18.4 20.7 24.5 26 25.2 24.1 23.7 23.5 23.1 22.7 22.5 21.7 20.5 21.9 22.9 21.5 19 17 16.1 15.9 15.7 15.1 14.8 14.3 14.5 18.9 21.6 20.4 17.9 15.7 14.5 14 13.9 14.4 15.8 15.6 14.7 16.7 17.9 18.7 20.1 19.5 19.4 18.6 17.8 17.1 16.5 15.5 14.9 18.6 19.1 18.8 18.2 18 19 20.7 21.2 20.7 19.6 18.6 18.7 23.8 24.9 24.8 23.8 22.3 21.7 20.7 19.7 18.4 17.4 17 18 23.8 25.5 25.6 23.7 22 21.3 20.7 20.4 20.3 20.4 19.8 19.5 23.1 23.5 23.5 22.9 21.9 21.5 20.5 20.2 19.4 19.2 18.8 18.8 22.6 23.3 23 etc...

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 20.1532710280374 0.215413105816944 93.5563829861096 Geometric Mean 19.8925708262132 Harmonic Mean 19.6154079869352 Quadratic Mean 20.3970127921007 Winsorized Mean ( 1 / 71 ) 20.1523364485981 0.215158402901589 93.6627906548256 Winsorized Mean ( 2 / 71 ) 20.1560747663551 0.214269132367680 94.0689615141013 Winsorized Mean ( 3 / 71 ) 20.1630841121495 0.212797441677222 94.7524742460653 Winsorized Mean ( 4 / 71 ) 20.1612149532710 0.212087460430038 95.0608532554975 Winsorized Mean ( 5 / 71 ) 20.1705607476636 0.210745542658416 95.710497566047 Winsorized Mean ( 6 / 71 ) 20.1705607476636 0.210038562889562 96.0326545286314 Winsorized Mean ( 7 / 71 ) 20.1705607476636 0.207633942506479 97.1448141097364 Winsorized Mean ( 8 / 71 ) 20.1705607476636 0.207633942506479 97.1448141097364 Winsorized Mean ( 9 / 71 ) 20.1747663551402 0.207079504866043 97.4252201742076 Winsorized Mean ( 10 / 71 ) 20.1700934579439 0.206583357842974 97.6365844206843 Winsorized Mean ( 11 / 71 ) 20.1752336448598 0.205913771500218 97.9790399538114 Winsorized Mean ( 12 / 71 ) 20.1752336448598 0.205913771500218 97.9790399538114 Winsorized Mean ( 13 / 71 ) 20.1691588785047 0.205278744869118 98.2525438343077 Winsorized Mean ( 14 / 71 ) 20.1691588785047 0.202264203366856 99.7168977148316 Winsorized Mean ( 15 / 71 ) 20.1691588785047 0.200679839707392 100.504160796186 Winsorized Mean ( 16 / 71 ) 20.1616822429907 0.198289479781321 101.678022783788 Winsorized Mean ( 17 / 71 ) 20.1696261682243 0.197306050910035 102.225076601533 Winsorized Mean ( 18 / 71 ) 20.1780373831776 0.196277876877493 102.803421884228 Winsorized Mean ( 19 / 71 ) 20.1957943925234 0.194148201349976 104.022567564857 Winsorized Mean ( 20 / 71 ) 20.1864485981308 0.193251434428696 104.456914681164 Winsorized Mean ( 21 / 71 ) 20.2060747663551 0.190950899771517 105.818169961665 Winsorized Mean ( 22 / 71 ) 20.2060747663551 0.188790219035958 107.029245845128 Winsorized Mean ( 23 / 71 ) 20.2168224299065 0.187567105231099 107.784477480727 Winsorized Mean ( 24 / 71 ) 20.2056074766355 0.186514630073728 108.332560661050 Winsorized Mean ( 25 / 71 ) 20.2172897196262 0.185198056488684 109.165776914411 Winsorized Mean ( 26 / 71 ) 20.2172897196262 0.18271748458323 110.647811104344 Winsorized Mean ( 27 / 71 ) 20.242523364486 0.179954059666688 112.487172570484 Winsorized Mean ( 28 / 71 ) 20.2948598130841 0.174451027580709 116.335570472319 Winsorized Mean ( 29 / 71 ) 20.3084112149533 0.173077412963868 117.337154901853 Winsorized Mean ( 30 / 71 ) 20.3224299065421 0.171677920087438 118.375326869009 Winsorized Mean ( 31 / 71 ) 20.3369158878505 0.170253946021485 119.450481842483 Winsorized Mean ( 32 / 71 ) 20.3518691588785 0.165954838927312 122.634984857492 Winsorized Mean ( 33 / 71 ) 20.3518691588785 0.165954838927312 122.634984857492 Winsorized Mean ( 34 / 71 ) 20.3518691588785 0.165954838927312 122.634984857492 Winsorized Mean ( 35 / 71 ) 20.3355140186916 0.161353834006322 126.030559756608 Winsorized Mean ( 36 / 71 ) 20.3355140186916 0.161353834006322 126.030559756608 Winsorized Mean ( 37 / 71 ) 20.3528037383178 0.159738864123429 127.41297398103 Winsorized Mean ( 38 / 71 ) 20.3705607476636 0.158106565984782 128.840700705777 Winsorized Mean ( 39 / 71 ) 20.3887850467290 0.156458454673968 130.314370605383 Winsorized Mean ( 40 / 71 ) 20.3700934579439 0.154726663650041 131.652121085069 Winsorized Mean ( 41 / 71 ) 20.3509345794393 0.152978904268681 133.030986701907 Winsorized Mean ( 42 / 71 ) 20.3509345794393 0.152978904268681 133.030986701907 Winsorized Mean ( 43 / 71 ) 20.4313084112150 0.145931938894312 140.005735317557 Winsorized Mean ( 44 / 71 ) 20.4313084112150 0.142315192465572 143.563790044114 Winsorized Mean ( 45 / 71 ) 20.4313084112150 0.142315192465572 143.563790044114 Winsorized Mean ( 46 / 71 ) 20.4098130841121 0.140366378481639 145.403858850586 Winsorized Mean ( 47 / 71 ) 20.4317757009346 0.138539484098050 147.479802122506 Winsorized Mean ( 48 / 71 ) 20.4317757009346 0.138539484098050 147.479802122506 Winsorized Mean ( 49 / 71 ) 20.4088785046729 0.136483759037813 149.533385133528 Winsorized Mean ( 50 / 71 ) 20.4088785046729 0.136483759037813 149.533385133528 Winsorized Mean ( 51 / 71 ) 20.4327102803738 0.134526197425663 151.886477662944 Winsorized Mean ( 52 / 71 ) 20.4084112149533 0.132363818055547 154.184213743282 Winsorized Mean ( 53 / 71 ) 20.4331775700935 0.130353794659436 156.751689687880 Winsorized Mean ( 54 / 71 ) 20.4079439252336 0.123896249782167 164.718011732515 Winsorized Mean ( 55 / 71 ) 20.4079439252336 0.123896249782167 164.718011732515 Winsorized Mean ( 56 / 71 ) 20.4079439252336 0.119556360337170 170.697266692291 Winsorized Mean ( 57 / 71 ) 20.3813084112150 0.117280292691348 173.782891767276 Winsorized Mean ( 58 / 71 ) 20.3542056074766 0.114998976036067 176.994668205507 Winsorized Mean ( 59 / 71 ) 20.3542056074766 0.114998976036067 176.994668205507 Winsorized Mean ( 60 / 71 ) 20.3822429906542 0.108256059360361 188.278079869932 Winsorized Mean ( 61 / 71 ) 20.3822429906542 0.108256059360361 188.278079869932 Winsorized Mean ( 62 / 71 ) 20.3532710280374 0.105864697897366 192.257394885021 Winsorized Mean ( 63 / 71 ) 20.3532710280374 0.105864697897366 192.257394885021 Winsorized Mean ( 64 / 71 ) 20.3532710280374 0.105864697897366 192.257394885021 Winsorized Mean ( 65 / 71 ) 20.3228971962617 0.103395238328834 196.555446118588 Winsorized Mean ( 66 / 71 ) 20.3228971962617 0.0985189125254028 206.284221732771 Winsorized Mean ( 67 / 71 ) 20.3228971962617 0.0985189125254028 206.284221732771 Winsorized Mean ( 68 / 71 ) 20.2911214953271 0.095998790958064 211.368510924175 Winsorized Mean ( 69 / 71 ) 20.2911214953271 0.095998790958064 211.368510924175 Winsorized Mean ( 70 / 71 ) 20.2911214953271 0.0909045523533675 223.213480183596 Winsorized Mean ( 71 / 71 ) 20.2911214953271 0.0909045523533675 223.213480183596 Trimmed Mean ( 1 / 71 ) 20.1532710280374 0.212381280588801 94.8919366724077 Trimmed Mean ( 2 / 71 ) 20.1632075471698 0.209435719587802 96.2739669568006 Trimmed Mean ( 3 / 71 ) 20.1836538461538 0.206798943932410 97.6003719475023 Trimmed Mean ( 4 / 71 ) 20.1836538461538 0.204555765574209 98.6706670892225 Trimmed Mean ( 5 / 71 ) 20.1985294117647 0.202380641971382 99.8046513491194 Trimmed Mean ( 6 / 71 ) 20.2044554455446 0.200391591794769 100.824866276011 Trimmed Mean ( 7 / 71 ) 20.2044554455446 0.198422671418019 101.825337302206 Trimmed Mean ( 8 / 71 ) 20.2105 0.196757218587260 102.717959448267 Trimmed Mean ( 9 / 71 ) 20.2229591836735 0.194985990431383 103.714934282882 Trimmed Mean ( 10 / 71 ) 20.2288659793814 0.193182668928851 104.713668630552 Trimmed Mean ( 11 / 71 ) 20.2354166666667 0.19132865093525 105.762605693147 Trimmed Mean ( 12 / 71 ) 20.2415789473684 0.189438597110174 106.850342306939 Trimmed Mean ( 13 / 71 ) 20.2478723404255 0.187423830543374 108.03253930796 Trimmed Mean ( 14 / 71 ) 20.2478723404255 0.185345146056105 109.244146778445 Trimmed Mean ( 15 / 71 ) 20.2548387096774 0.183449958773086 110.410701889179 Trimmed Mean ( 16 / 71 ) 20.2619565217391 0.181587292733129 111.582458313959 Trimmed Mean ( 17 / 71 ) 20.2772222222222 0.17982823475022 112.758834842521 Trimmed Mean ( 18 / 71 ) 20.2848314606742 0.178040378395552 113.933881984947 Trimmed Mean ( 19 / 71 ) 20.2920454545455 0.176221973329938 115.150483626425 Trimmed Mean ( 20 / 71 ) 20.2982758620690 0.174467257931246 116.344327885683 Trimmed Mean ( 21 / 71 ) 20.3052325581395 0.172661001355691 117.601730551242 Trimmed Mean ( 22 / 71 ) 20.3111764705882 0.170922108071783 118.832939165822 Trimmed Mean ( 23 / 71 ) 20.3172619047619 0.169233155762321 120.054854577648 Trimmed Mean ( 24 / 71 ) 20.3228915662651 0.167518779583843 121.317094219240 Trimmed Mean ( 25 / 71 ) 20.3292682926829 0.165755597666656 122.646043807017 Trimmed Mean ( 26 / 71 ) 20.3351851851852 0.163963522378214 124.022617288485 Trimmed Mean ( 27 / 71 ) 20.3351851851852 0.162225548350856 125.351311133835 Trimmed Mean ( 28 / 71 ) 20.34125 0.160568298759235 126.682851828061 Trimmed Mean ( 29 / 71 ) 20.3462025316456 0.159199525697177 127.803160483953 Trimmed Mean ( 30 / 71 ) 20.3487179487179 0.157820350971459 128.935956760088 Trimmed Mean ( 31 / 71 ) 20.3506493506494 0.15642945016189 130.094744497205 Trimmed Mean ( 32 / 71 ) 20.3519736842105 0.155025282391171 131.28164238951 Trimmed Mean ( 33 / 71 ) 20.3527027027027 0.153809402119956 132.324177990300 Trimmed Mean ( 34 / 71 ) 20.3527397260274 0.152485919978426 133.472911655758 Trimmed Mean ( 35 / 71 ) 20.3527777777778 0.151045130197230 134.746335424398 Trimmed Mean ( 36 / 71 ) 20.3535211267606 0.149803127127721 135.868466279795 Trimmed Mean ( 37 / 71 ) 20.3542857142857 0.14844646495774 137.115327873117 Trimmed Mean ( 38 / 71 ) 20.3543478260870 0.147079612899421 138.390001338976 Trimmed Mean ( 39 / 71 ) 20.3536764705882 0.145700576691332 139.695236167169 Trimmed Mean ( 40 / 71 ) 20.3522388059701 0.144306981861333 141.034332112406 Trimmed Mean ( 41 / 71 ) 20.3515151515152 0.142904040216689 142.413854224524 Trimmed Mean ( 42 / 71 ) 20.3515384615385 0.141489792908107 143.837502644138 Trimmed Mean ( 43 / 71 ) 20.3515625 0.139934533585225 145.436312099509 Trimmed Mean ( 44 / 71 ) 20.3484126984127 0.138727706926865 146.67879365396 Trimmed Mean ( 45 / 71 ) 20.3451612903226 0.137649877015638 147.803701183193 Trimmed Mean ( 46 / 71 ) 20.3418032786885 0.136452232341803 149.076368554629 Trimmed Mean ( 47 / 71 ) 20.3391666666667 0.135267635079152 150.362403059425 Trimmed Mean ( 48 / 71 ) 20.335593220339 0.134078347865192 151.669479406066 Trimmed Mean ( 49 / 71 ) 20.3318965517241 0.132751976118304 153.157016160761 Trimmed Mean ( 50 / 71 ) 20.3289473684211 0.131433781123370 154.67064246854 Trimmed Mean ( 51 / 71 ) 20.3258928571429 0.129961047127415 156.399885245732 Trimmed Mean ( 52 / 71 ) 20.3218181818182 0.128462920585179 158.192092233677 Trimmed Mean ( 53 / 71 ) 20.3185185185185 0.126964644782839 160.032885952396 Trimmed Mean ( 54 / 71 ) 20.3185185185185 0.125438592123683 161.979803619642 Trimmed Mean ( 55 / 71 ) 20.3141509433962 0.124252193832547 163.491285882431 Trimmed Mean ( 56 / 71 ) 20.3105769230769 0.122907725850794 165.250612054553 Trimmed Mean ( 57 / 71 ) 20.3068627450980 0.121742027304137 166.802403366976 Trimmed Mean ( 58 / 71 ) 20.303 0.120609295437844 168.336942242260 Trimmed Mean ( 59 / 71 ) 20.3 0.119510874190207 169.859020256948 Trimmed Mean ( 60 / 71 ) 20.2979166666667 0.118249209421251 171.653719851584 Trimmed Mean ( 61 / 71 ) 20.2957446808511 0.117377312875037 172.910285503455 Trimmed Mean ( 62 / 71 ) 20.2923913043478 0.116358012733125 174.396166002678 Trimmed Mean ( 63 / 71 ) 20.2888888888889 0.115392902689336 175.824408746448 Trimmed Mean ( 64 / 71 ) 20.2863636363636 0.114261567409658 177.543194061321 Trimmed Mean ( 65 / 71 ) 20.2809523809524 0.112939092619170 179.574245822389 Trimmed Mean ( 66 / 71 ) 20.2792682926829 0.111648265345712 181.635319007325 Trimmed Mean ( 67 / 71 ) 20.2775 0.110622161695692 183.304138060336 Trimmed Mean ( 68 / 71 ) 20.2756410256410 0.109401330006141 185.332673967519 Trimmed Mean ( 69 / 71 ) 20.275 0.108225317270247 187.340638137117 Trimmed Mean ( 70 / 71 ) 20.2743243243243 0.106821410834636 189.796447789946 Trimmed Mean ( 71 / 71 ) 20.2736111111111 0.105724141585861 191.759524428453 Median 20.35 Midrange 19.1 Midmean - Weighted Average at Xnp 20.2943925233645 Midmean - Weighted Average at X(n+1)p 20.3422018348624 Midmean - Empirical Distribution Function 20.3422018348624 Midmean - Empirical Distribution Function - Averaging 20.3422018348624 Midmean - Empirical Distribution Function - Interpolation 20.3141509433962 Midmean - Closest Observation 20.3422018348624 Midmean - True Basic - Statistics Graphics Toolkit 20.3422018348624 Midmean - MS Excel (old versions) 20.3422018348624 Number of observations 214

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/29/t1262122259arblnw2vn5drvw0/12oxh1262121730.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/29/t1262122259arblnw2vn5drvw0/12oxh1262121730.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/29/t1262122259arblnw2vn5drvw0/27fme1262121730.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/29/t1262122259arblnw2vn5drvw0/27fme1262121730.ps (open in new window)

Parameters (Session):

Parameters (R input):

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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