Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_percentiles.wasp
Title produced by softwarePercentiles
Date of computationMon, 24 Aug 2020 15:17:27 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Aug/24/t1598275081l2iuytbmwqfkchc.htm/, Retrieved Fri, 29 Mar 2024 13:09:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319218, Retrieved Fri, 29 Mar 2024 13:09:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Percentiles] [] [2020-08-24 13:17:27] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
786.90
914.57
819.57
756.01
667.94
787.91
1.007.33
804.47
960.63
807.76
926.00
880.33
902.20
812.88
910.00
784.18
824.96
884.73
938.10
867.28
832.90
951.26
696.79
731.28
616.76
725.26
797.72
795.04
801.83
759.59
749.72
804.32
858.94
773.12
711.41
762.32
691.17
651.17
835.31
799.50
766.51
682.74
776.26
805.48
828.47
864.31
675.87
818.82
713.02
734.69
751.66
688.63
695.60
732.01
828.23
689.06
732.55
748.19
924.55
737.59
715.66
716.56
814.82
739.14
773.87
732.18
747.89
758.58
622.32
829.14
761.02
796.69
732.62
717.43
724.51
748.71
702.53
662.32
756.92
651.77
742.12
748.97
822.37
727.38
695.45
701.11
810.41
786.78
782.34
777.36
745.96
697.50
707.62
598.64
687.61
703.41
761.60
687.67
811.35
725.59
666.35
703.68
858.09
732.66
768.65
613.64
723.12
1.029.42
740.67
915.22
711.20
667.64
714.44
722.64
785.94
774.57
842.11
752.71
770.54
799.48
758.58
813.83
749.63
766.55
618.35
775.90
693.86
743.53
683.55
791.12
745.37
871.55
833.94
784.71
725.73
816.31
1.022.45
723.69
818.50
688.79
898.51
713.85
897.91
733.94
766.35
668.08
815.81
769.24
769.99
714.87
748.93
701.93
719.99
740.30
752.71
749.40
722.53
843.35
738.30
1.041.66
700.41
719.68
803.62
712.08
857.47
893.42
851.35
820.47
748.08
735.41
748.41
835.09
804.42
845.07
815.42
675.39
781.17
743.58
725.01
750.55
1.016.51
753.13
696.12
816.40
806.51
766.81
745.43
679.16
737.80
680.71
879.71
882.93
772.23
881.16
873.95
895.79
739.32
871.77
710.31
737.72
773.26
713.63
810.82
780.10
733.67
783.35
779.45
747.47
716.46
731.57
905.35
753.40
702.01
598.66
775.78
699.41
768.76
695.89
830.36
701.57
724.16
713.46
839.61
744.31
733.43
722.06
765.60
702.27
840.86
713.85
656.38
688.59
747.89
777.20
768.23
801.64
747.47
702.93
728.49
737.43
732.18
764.14
831.18
663.51
801.18
782.42
741.01
646.29
793.63
762.34
732.21
703.95
775.03
841.25
727.25
757.39
731.26
756.00
747.21
653.99
754.50
1.061.74
770.32
715.75
858.00
764.13
704.48
587.27
721.94
700.43
534.86
690.52
769.09
751.19
713.09
685.87
757.04
846.45
812.17
749.05
739.05
751.89
733.00
758.77
684.60
754.54
754.16
715.64
707.42
839.61
818.86
807.69
785.05
836.24
797.37
606.24
731.34
743.73
737.08
728.89
804.44
750.42
820.34
603.41
752.78
726.10
711.24
687.63
738.57
851.89
750.27
784.28
945.89
718.92
769.39
731.12
774.03
797.74
754.63
769.57
634.28
691.29
655.76
803.15
709.77
717.00
742.70
726.08
993.29
769.07
745.02
756.55
875.17
643.12
1.016.18
584.51
727.84
693.67
759.79
743.13
1.052.46
841.76
781.12
775.04
786.52
773.00
732.45
743.91
857.96
739.01
771.95
660.38
883.63
774.18
693.19
757.73
696.66
747.38
726.25
667.81
835.49
838.48
797.36
721.51
754.82
708.74
687.49
796.64
900.36
748.53
872.64
803.02
840.59
910.05
930.61
1.037.80
986.71
826.60
692.00
767.01
980.42
880.98
793.29
727.92
762.28
819.60
775.10
777.52
776.06
714.19
909.32
676.65
732.13
803.76
774.11
663.31
765.14
823.95
799.36
756.56
988.67
756.93
1.008.94
949.58
808.64
754.66
796.01
670.84
931.84
768.37
796.89
694.74
812.52
923.79
933.64
790.98
870.49
656.45
782.35
671.99
959.98
974.72
802.27
777.60
805.69
857.82
736.62
803.86
765.32
924.36
708.80
834.14
958.22
719.70
722.17
1.061.76
691.61
902.78
824.25
856.35
787.23
751.16
736.32
812.28
699.73
989.74
677.59
697.18
742.72
745.89
857.38
783.29
777.87
760.61
700.22
955.41
888.86
739.54
763.13
749.04
729.08
714.57
966.98
783.72
715.71
789.22
737.26
663.22
675.57
677.84
687.33
858.67
815.28
616.40
677.87
719.09
700.98
642.11
693.37
734.97
711.35
611.04
728.11
774.35
751.75
747.92
715.11
928.06
915.37
729.08
725.06
717.38
664.00
708.88
714.23
1.028.35
894.23
741.20
877.88
903.10
753.13
926.94
765.22
927.50
952.19
835.07
751.44
723.02
786.45
795.07
695.58
675.78
740.30
1.045.56
859.22
800.05
864.67
757.55
817.52
770.72
769.48
401.01
758.88
848.41
738.57
895.11
776.61
728.31
964.13
910.22
793.71
928.17
696.16
807.23
816.89
824.40
758.38
888.64
850.68
799.68
854.80
869.47
918.94
810.25
829.50
756.80
800.86
904.84
723.95
673.51
849.11
775.86
755.49
607.16
744.71
696.48
765.83
678.24
810.56
836.93
756.65
733.67
827.77
812.56
750.40
812.27
781.85
806.38
701.41
731.95
636.54
746.93
729.32
693.94
734.99
802.74
781.99
645.62
785.30
846.54
737.91
804.19
812.75
795.57
749.20
739.40
716.49
738.72
731.07
730.75
658.57
718.77
849.55
649.65
690.56
678.98
968.69
703.28
736.34
717.80
842.98
760.11
685.98
709.05
880.08
699.06
842.69
743.81
865.96
724.51
716.35
741.90
666.01
719.75
834.17
756.81
750.25
747.03
741.47
837.25
696.93
874.05
732.25
770.27
727.80
604.75
724.92
706.33
753.35
727.52
692.36
804.08
694.74
855.66
911.69
725.69
681.82
696.46
729.01
661.43
663.75
801.65
633.72
669.07
874.02
655.61
646.00
656.80
809.49
652.54
661.05




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319218&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319218&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319218&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
x <-sort(x[!is.na(x)])
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]
}
}
}
}
lx <- length(x)
qval <- array(NA,dim=c(99,8))
mystep <- 25
mystart <- 25
if (lx>10){
mystep=10
mystart=10
}
if (lx>20){
mystep=5
mystart=5
}
if (lx>50){
mystep=2
mystart=2
}
if (lx>=100){
mystep=1
mystart=1
}
for (perc in seq(mystart,99,mystep)) {
qval[perc,1] <- q1(x,lx,perc/100,i,f)
qval[perc,2] <- q2(x,lx,perc/100,i,f)
qval[perc,3] <- q3(x,lx,perc/100,i,f)
qval[perc,4] <- q4(x,lx,perc/100,i,f)
qval[perc,5] <- q5(x,lx,perc/100,i,f)
qval[perc,6] <- q6(x,lx,perc/100,i,f)
qval[perc,7] <- q7(x,lx,perc/100,i,f)
qval[perc,8] <- q8(x,lx,perc/100,i,f)
}
bitmap(file='test1.png')
myqqnorm <- qqnorm(x,col=2)
qqline(x)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Percentiles - Ungrouped Data',9,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p',1,TRUE)
a<-table.element(a, 'Weighted Average at Xnp',1,TRUE)
a<-table.element(a, 'Weighted Average at X(n+1)p',1,TRUE)
a<-table.element(a, 'Empirical Distribution Function',1,TRUE)
a<-table.element(a, 'Empirical Distribution Function - Averaging',1,TRUE)
a<-table.element(a, 'Empirical Distribution Function - Interpolation',1,TRUE)
a<-table.element(a, 'Closest Observation',1,TRUE)
a<-table.element(a, 'True Basic - Statistics Graphics Toolkit',1,TRUE)
a<-table.element(a, 'MS Excel (old versions)',1,TRUE)
a<-table.row.end(a)
for (perc in seq(mystart,99,mystep)) {
a<-table.row.start(a)
a<-table.element(a,round(perc/100,2),1,TRUE)
for (j in 1:8) {
a<-table.element(a,signif(qval[perc,j],6))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')