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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 07 Dec 2014 09:13:56 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/07/t1417943647x5gqwiqocohle4i.htm/, Retrieved Thu, 16 May 2024 11:54:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263687, Retrieved Thu, 16 May 2024 11:54:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [dtyu] [2014-12-07 09:13:56] [627bde65e5570be47fd7fc8a9f75ea40] [Current]
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Dataseries X:
1	12.9	143.872	-148.717
2	7.4	133.848	-598.482
3	12.2	135.214	-132.144
4	12.8	139.656	-116.562
5	7.4	140.436	-664.356
6	6.7	135.876	-68.876
7	12.6	152.583	-265.834
8	14.8	137.093	109.069
9	13.3	146.604	-13.604
10	11.1	145.874	-348.738
11	8.2	151.127	-691.265
12	11.4	138.806	-24.806
13	6.4	140.663	-766.635
14	10.6	121.998	-159.978
15	12	150.341	-303.415
16	6.3	107.533	-445.331
17	11.3	116.782	-0.378153
18	11.9	145.643	-266.428
19	9.3	128.342	-35.342
20	9.6	137.864	-418.636
21	10	119.983	-199.827
22	6.4	127.359	-633.589
23	13.8	14.805	-100.504
24	10.8	145.009	-370.088
25	13.8	145.668	-0.766779
26	11.7	142.012	-250.124
27	10.9	150.139	-411.392
28	16.1	162.375	-0.137491
29	13.4	126.123	0.787701
30	9.9	137.611	-386.111
31	11.5	125.611	-106.114
32	8.3	119.026	-360.259
33	11.7	137.589	-205.888
34	6.1	12.943	-684.304
35	9	12.904	-390.405
36	9.7	14.772	-507.204
37	10.8	128.346	-203.459
38	10.3	131.225	-282.251
39	10.4	12.407	-200.703
40	12.7	128.973	-0.197251
41	9.3	152.456	-594.562
42	11.8	137.387	-193.865
43	5.9	133.107	-741.071
44	11.4	142.868	-288.683
45	13	142.506	-125.056
46	10.8	130.661	-226.609
47	12.3	114.538	0.846225
48	11.3	148.832	-358.321
49	11.8	13.147	-1.347
50	7.9	129.699	-506.989
51	12.7	117.706	0.929353
52	12.3	122.476	0.0523525
53	11.6	124.948	-0.894814
54	6.7	110.425	-434.246
55	10.9	13.09	-218.998
56	12.1	127.988	-0.698753
57	13.3	135.871	-0.287139
58	10.1	127.125	-261.249
59	5.7	121.721	-647.212
60	14.3	12.95	134.996
61	8	101.572	-21.572
62	13.3	130.243	0.275668
63	9.3	148.981	-559.815
64	12.5	133.998	-0.899793
65	7.6	117.978	-419.782
66	15.9	15.122	0.77795
67	9.2	142.057	-500.571
68	9.1	118.245	-272.451
69	11.1	149.214	-382.137
70	13	158.183	-281.827
71	14.5	14.314	0.18602
72	12.2	125.668	-0.366754
73	12.3	157.745	-347.445
74	11.4	127.784	-137.844
75	8.8	123.886	-358.862
76	14.6	143.273	0.272735
77	7.3	145.447	-724.472
78	12.6	124.361	0.163925
79	NA	NA	-0.925255
80	13	134.417	-0.441745
81	12.6	134.237	-0.823672
82	13.2	147.367	-153.668
83	9.9	151.307	-523.075
84	7.7	977.628	-207.628
85	10.5	878.813	171.187
86	13.4	147.683	-136.833
87	10.9	182.088	-73.088
88	4.3	705.706	-275.706
89	10.3	12.104	-180.405
90	11.8	129.616	-116.164
91	11.2	115.181	-0.318068
92	11.4	15.12	-372.002
93	8.6	772.997	0.87003
94	13.2	124.612	0.73883
95	12.6	190.829	-648.291
96	5.6	861.822	-301.822
97	9.9	130.231	-312.313
98	8.8	133.481	-454.813
99	7.7	106.379	-293.794
100	9	147.512	-575.124
101	7.3	786.817	-0.568166
102	11.4	974.484	165.516
103	13.6	185.401	-494.009
104	7.9	880.026	-0.900264
105	10.7	122.319	-153.187
106	10.3	130.075	-270.748
107	8.3	114.826	-318.264
108	9.6	772.627	187.373
109	14.2	181.251	-392.515
110	8.5	713.314	136.686
111	13.5	199.362	-643.617
112	4.9	942.525	-452.525
113	6.4	931.347	-291.347
114	9.6	103.246	-0.724639
115	11.6	12.349	-0.749004
116	11.1	186.042	-750.419
117	4.4	36.527	0.747298
118	12.7	791.255	478.745
119	18.1	137.015	439.855
120	17.9	165.283	137.174
121	16.6	154.732	112.684
122	12.6	11.498	110.205
123	17.1	134.616	363.841
124	19.1	197.166	-0.616571
125	16.1	137.326	236.735
126	13.4	945.741	394.259
127	18.4	141.727	422.733
128	14.7	168.765	-21.765
129	10.6	992.254	0.677463
130	12.6	938.103	321.897
131	16.2	17.358	-115.804
132	13.6	972.655	387.345
133	18.9	174.874	141.261
134	14.1	123.115	178.855
135	14.5	137.745	0.725477
136	16.2	139.235	227.654
137	14.8	129.362	186.377
138	14.8	140.282	0.771773
139	12.5	125.731	-0.0731446
140	12.7	801.864	468.136
141	17.4	192.213	-182.131
142	8.6	401.095	458.905
143	18.4	169.145	148.553
144	16.1	161.965	-0.0964733
145	11.6	673.041	486.959
146	17.8	159.173	188.265
147	15.3	101.096	519.037
148	17.7	149.175	278.245
149	15.6	129.369	266.313
150	16.4	132.499	315.006
151	17.7	177.621	-0.0620881
152	13.6	144.536	-0.853567
153	11.7	10.249	145.099
154	14.4	121.596	224.037
155	14.8	108.976	390.238
156	18.3	210.878	-278.781
157	9.9	804.132	185.868
158	16	118.067	419.332
159	18.3	151.648	313.517
160	16.9	142.604	263.962
161	14.6	133.033	129.668
162	13.9	104.245	347.547
163	19	160.921	290.794
164	15.6	150.577	0.542306
165	14.9	153.588	-0.458804
166	11.8	720.677	459.323
167	18.5	143.846	41.154
168	15.9	133.231	25.769
169	17.1	115.016	55.984
170	16.1	124.884	361.161
171	19.9	209.087	-100.871
172	11	600.959	499.041
173	18.5	154.593	304.068
174	15.1	132.848	181.519
175	15	16.06	-1.06
176	11.4	824.709	315.291
177	16	112.693	473.073
178	18.1	175.292	0.570781
179	14.6	13.027	157.297
180	15.4	137.224	167.759
181	15.4	103.278	507.219
182	17.6	179.341	-0.334132
183	13.4	760.665	579.335
184	19.1	173.105	178.946
185	15.4	189.818	-358.182
186	7.6	821.218	-0.612185
187	13.4	126.179	0.78207
188	13.9	886.506	503.494
189	19.1	161.111	298.885
190	15.3	151.872	0.112848
191	12.9	103.664	253.358
192	16.1	113.497	475.031
193	17.4	171.362	0.263829
194	13.2	138.741	-0.674072
195	12.2	107.964	140.364
196	12.6	141.533	-155.335
197	10.4	682.464	357.536
198	15.4	173.445	-194.452
199	9.6	39.068	56.932
200	18.2	167.654	143.458
201	13.6	123.838	121.625
202	14.9	137.234	117.659
203	14.8	125.257	227.425
204	14.1	113.509	274.908
205	14.9	11.765	313.501
206	16.3	151.108	118.923
207	19.3	181.467	115.331
208	13.6	127.637	0.83625
209	13.6	101.982	340.178
210	15.7	147.065	0.993508
211	12.8	100.343	276.566
212	14.6	158.321	-12.321
213	9.9	931.265	0.58735
214	12.7	122.523	0.447675
215	11.9	48.573	70.427
216	19.2	152.126	39.874
217	16.6	168.475	-0.247543
218	11.2	890.529	229.471
219	15.3	160.301	-0.730149
220	11.9	957.081	232.919
221	13.2	105.991	260.086
222	16.4	168.019	-0.401885
223	12.4	929.452	310.548
224	15.9	152.556	0.64438
225	14.4	961.431	478.569
226	18.2	186.393	-0.439271
227	11.2	926.606	193.394
228	15.7	108.115	488.852
229	17.8	204.104	-261.042
230	7.7	823.854	-0.53854
231	12.4	833.967	406.033
232	15.6	981.642	578.358
233	19.3	157.198	358.019
234	15.2	103.449	485.508
235	17.1	142.369	286.312
236	15.6	103.976	520.237
237	18.4	123.704	602.958
238	19.1	135.835	551.647
239	18.6	138.443	47.557
240	19.1	175.511	154.888
241	13.1	133.385	-0.238452
242	12.9	142.792	-137.921
243	9.5	166.004	-710.038
244	4.5	318.699	131.301
245	11.9	117.984	0.101569
246	13.6	14.662	-106.203
247	11.7	111.668	0.533218
248	12.4	117.621	0.637858
249	13.4	126.368	0.763205
250	11.4	936.706	203.294
251	14.9	107.377	41.623
252	19.9	151.105	478.954
253	17.8	195.104	-171.035
254	11.2	91.463	20.537
255	14.6	108.754	372.464
256	17.6	16.735	0.864958
257	14.1	108.948	320.521
258	16.1	151.926	0.907409
259	13.4	142.175	-0.817468
260	11.9	120.753	-0.17533
261	12	974.481	225.519
262	14.8	119.168	288.323
263	15.2	156.128	-0.41281
264	13.2	998.526	321.474
265	16.9	202.967	-339.674
266	7.9	116.799	-377.986
267	7.7	80.126	-0.312602
268	12.6	177.962	-519.623
269	7.9	981.176	-191.176
270	11	105.757	0.424307
271	12.4	156.523	-325.229
272	10	800.155	199.845
273	14.9	107.393	416.074
274	16.7	153.896	131.042
275	13.4	116.878	171.215
276	14	104.012	359.883
277	15.7	117.897	391.027
278	16.9	173.186	-0.418556
279	11	750.915	349.085
280	15.4	147.676	0.63238
281	12.2	866.561	353.439
282	15.1	10.599	450.101
283	17.8	154.829	231.706
284	15.2	140.528	114.716
285	14.6	107.188	388.117
286	16.7	193.941	-269.405
287	8	NA	NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263687&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263687&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263687&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net



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('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('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('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('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('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('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('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('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('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('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')