::Free Statistics and Forecasting Software::

All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

This free online software (calculator) computes a series of graphical tools for the purpose of Explorative Data Analysis. If we consider the model

response = constant + random component

then the following assumptions can be tested by the use of this software module:

are the data autocorrelated? (The model assumes no autocorrelation) is the random component generated by a fixed distribution? (The model assumes a fixed distribution) is the deterministic component constant? (The model assumes that the distribution has a fixed location) does the random component have a fixed variation? (The model assumes a distribution with fixed variation)

Enter (or paste) your data delimited by hard returns.

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112 118 132 129 121 135 148 148 136 119 104 118 115 126 141 135 125 149 170 170 158 133 114 140 145 150 178 163 172 178 199 199 184 162 146 166 171 180 193 181 183 218 230 242 209 191 172 194 196 196 236 235 229 243 264 272 237 211 180 201 204 188 235 227 234 264 302 293 259 229 203 229 242 233 267 269 270 315 364 347 312 274 237 278 284 277 317 313 318 374 413 405 355 306 271 306 315 301 356 348 355 422 465 467 404 347 305 336 340 318 362 348 363 435 491 505 404 359 310 337 360 342 406 396 420 472 548 559 463 407 362 405 417 391 419 461 472 535 622 606 508 461 390 432
Sample Range: (leave blank to include all observations)
From:
To:
bandwidth of density plot (?)
# lags (autocorrelation function) (?)
0123456789101112131415161718192021222324252627282930313233343536
Chart options
Width:
Height:

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Click here to edit the underlying code of this R Module.

Source code of R module

par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) library(lattice) bitmap(file="pic1.png") plot(x,type="l",main="Run Sequence Plot",xlab="time or index",ylab="value") grid() dev.off() bitmap(file="pic2.png") hist(x) grid() dev.off() bitmap(file="pic3.png") if (par1 > 0) { densityplot(~x,col="black",main=paste("Density Plot bw = ",par1),bw=par1) } else { densityplot(~x,col="black",main="Density Plot") } dev.off() bitmap(file="pic4.png") qqnorm(x) qqline(x) grid() dev.off() if (par2 > 0) { bitmap(file="lagplot1.png") dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main="Lag plot (k=1), lowess, and regression line") lines(lowess(z)) abline(lm(z)) dev.off() if (par2 > 1) { bitmap(file="lagplotpar2.png") dum <- cbind(lag(x,k=par2),x) dum dum1 <- dum[(par2+1):length(x),] dum1 z <- as.data.frame(dum1) z mylagtitle <- "Lag plot (k=" mylagtitle <- paste(mylagtitle,par2,sep="") mylagtitle <- paste(mylagtitle,"), and lowess",sep="") plot(z,main=mylagtitle) lines(lowess(z)) dev.off() } bitmap(file="pic5.png") acf(x,lag.max=par2,main="Autocorrelation Function") grid() dev.off() } summary(x) load(file="createtable") a<-table.start() a<-table.row.start(a) a<-table.element(a,"Descriptive Statistics",2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"# observations",header=TRUE) a<-table.element(a,length(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"minimum",header=TRUE) a<-table.element(a,min(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"Q1",header=TRUE) a<-table.element(a,quantile(x,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"median",header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"mean",header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"Q3",header=TRUE) a<-table.element(a,quantile(x,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,"maximum",header=TRUE) a<-table.element(a,max(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file="mytable.tab")

Cite this software as:

Wessa P., (2012), Univariate Explorative Data Analysis (v1.0.9) in Free Statistics Software (v1.1.23-r7), Office for Research Development and Education, URL http://www.wessa.net/rwasp_edauni.wasp/

The R code is based on :

NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/, 2006-10-03.

Diethelm Wuertz, et. al.(2006)., fExtremes: Rmetrics - Extreme Financial Market Data. R package, version 221.10065., http://www.rmetrics.org

Deepayan Sarkar (2006). lattice: Lattice Graphics. R package version 0.13-8.

Bell Lab Trellis Page: URL: http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/

Cleveland, W.S. (1993), Visualizing Data

Becker, R.A., Cleveland, W.S. and Shyu, M., The Visual Design and Control of Trellis Display, Journal of Computational and Graphical Statistics

To cite Wessa.net in publications use:
Wessa, P. (2017), Free Statistics Software, Office for Research Development and Education,
version 1.1.23-r7, URL http://www.wessa.net/

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Software Version : 1.1.23-r7
Algorithms & Software : Patrick Wessa, PhD
Server : wessa.net

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