Draw Error Bars R
Contents |
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site how to draw error bars in excel About Us Learn more about Stack Overflow the company Business Learn more about how to draw error bars in excel 2010 hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join how to draw error bars in matlab the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up Scatter plot with error bars how to draw error bars on a line graph up vote 21 down vote favorite 11 How can I generate the following plot in R? Points, shown in the plot are the averages, and their ranges correspond to minimal and maximal values. I have data in two files (below is an example). x y 1 0.8773 1 0.8722 1 0.8816 1 0.8834 1 0.8759 1 0.8890 1 0.8727 2 0.9047 2 0.9062 2 0.8998
How To Draw Error Bars On A Bar Graph By Hand
2 0.9044 2 0.8960 .. ... r plot share|improve this question edited Oct 23 '12 at 15:10 Roland 73.2k463102 asked Oct 23 '12 at 14:29 sherlock85 1521313 Since you clearly don't want a boxplot, I changed the title of your question in order to reflect what you really want. –Roland Oct 23 '12 at 15:11 1 also plotrix::plotCI, gplots::plotCI, library("sos"); findFn("{error bar}") –Ben Bolker Oct 23 '12 at 17:29 add a comment| 5 Answers 5 active oldest votes up vote 51 down vote accepted First of all: it is very unfortunate and surprising that R cannot draw error bars "out of the box". Here is my favourite workaround, the advantage is that you do not need any extra packages. The trick is to draw arrows (!) but with little horizontal bars instead of arrowheads (!!!). This not-so-straightforward idea comes from the R Wiki Tips and is reproduced here as a worked-out example. Let's assume you have a vector of "average values" avg and another vector of "standard deviations" sdev, they are of the same length n. Let's make the abscissa just the number of these "measurements", so x <- 1:n. Using these
error bars Two within-subjects variables Note about normed means Helper functions Problem You want to plot means
How To Draw Error Bars In Excel 2013
and error bars for a dataset. Solution To make graphs barplot with error bars r with ggplot2, the data must be in a data frame, and in “long” (as opposed scatter plot with error bars in r to wide) format. If your data needs to be restructured, see this page for more information. Sample data The examples below will the ToothGrowth dataset. http://stackoverflow.com/questions/13032777/scatter-plot-with-error-bars Note that dose is a numeric column here; in some situations it may be useful to convert it to a factor. tg <- ToothGrowth head(tg) #> len supp dose #> 1 4.2 VC 0.5 #> 2 11.5 VC http://cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2)/ 0.5 #> 3 7.3 VC 0.5 #> 4 5.8 VC 0.5 #> 5 6.4 VC 0.5 #> 6 10.0 VC 0.5 library(ggplot2) First, it is necessary to summarize the data. This can be done in a number of ways, as described on this page. In this case, we’ll use the summarySE() function defined on that page, and also at the bottom of this page. (The code for the summarySE function must be entered before it is called here). # summarySE provides the standard deviation, standard error of the mean, and a (default 95%) confidence interval tgc <- summarySE(tg, measurevar="len", groupvars=c("supp","dose")) tgc #> supp dose N len sd se ci #> 1 OJ 0.5 10
|| is.character(x)) "" else as.character(substitute(y)), add=FALSE, lty=1, type='p', ylim=NULL, lwd=1, pch=16, Type=rep(1, length(y)), ...) Arguments x vector of numeric x-axis values (for vertical error bars) or a factor or character variable (for horizontal error bars, x representing the group labels) y vector of http://svitsrv25.epfl.ch/R-doc/library/Hmisc/html/errbar.html y-axis values. yplus vector of y-axis values: the tops of the error bars. yminus vector of y-axis values: the bottoms of the error bars. cap the width of the little lines at the tops and bottoms of the http://www.personality-project.org/r/html/error.bars.html error bars in units of the width of the plot. Defaults to 0.015. main a main title for the plot, see also title. sub a sub title for the plot. xlab optional x-axis labels if add=FALSE. ylab error bars optional y-axis labels if add=FALSE. Defaults to blank for horizontal charts. add set to TRUE to add bars to an existing plot (available only for vertical error bars) lty type of line for error bars type type of point. Use type="b" to connect dots. ylim y-axis limits. Default is to use range of y, yminus, and yplus. For horizonal charts, ylim is really the x-axis range, excluding differences. lwd line width for line segments (not main line) draw error bars pch character to use as the point. Type used for horizontal bars only. Is an integer vector with values 1 if corresponding values represent simple estimates, 2 if they represent differences. ... other parameters passed to all graphics functions. Details errbar adds vertical error bars to an existing plot or makes a new plot with error bars. It can also make a horizontal error bar plot that shows error bars for group differences as well as bars for groups. For the latter type of plot, the lower x-axis scale corresponds to group estimates and the upper scale corresponds to differences. The spacings of the two scales are identical but the scale for differences has its origin shifted so that zero may be included. If at least one of the confidence intervals includes zero, a vertical dotted reference line at zero is drawn. Author(s) Charles Geyer, University of Chicago. Modified by Frank Harrell, Vanderbilt University, to handle missing data, to add the parameters add and lty, and to implement horizontal charts with differences. Examples set.seed(1) x <- 1:10 y <- x + rnorm(10) delta <- runif(10) errbar( x, y, y + delta, y - delta ) # Show bootstrap nonparametric CLs for 3 group means and for # pairwise differences on same graph group <- sample(c('a','b','d'), 200, TRUE) y <- runif(200) + .25*(group=='b') + .5*(group=='d') cla <- smean.cl.boot(y[group=='a'],B=100,reps=TRUE) # usually
boxplot to summarize distributions. Means and standard errors are calculated from the raw data using describe. Alternatively, plots of means +/- one standard deviation may be drawn. Usage error.bars(x,stats=NULL, ylab = "Dependent Variable",xlab="Independent Variable", main=NULL,eyes=TRUE, ylim = NULL, xlim=NULL,alpha=.05,sd=FALSE, labels = NULL, pos = NULL, arrow.len = 0.05,arrow.col="black", add = FALSE,bars=FALSE,within=FALSE, col="blue",...) Arguments x A data frame or matrix of raw data stats Alternatively, a data.frame of descriptive stats from (e.g., describe) ylab y label xlab x label main title for figure ylim if specified, the limits for the plot, otherwise based upon the data xlim if specified, the x limits for the plot, otherwise c(.5,nvar + .5) eyes should 'cats eyes' plots be drawn alpha alpha level of confidence interval – defaults to 95% confidence interval sd if TRUE, draw one standard deviation instead of standard errors at the alpha level labels X axis label pos where to place text: below, left, above, right arrow.len How long should the top of the error bars be? arrow.col What color should the error bars be? add add=FALSE, new plot, add=TRUE, just points and error bars bars bars=TRUE will draw a bar graph if you really want to do that within should the error variance of a variable be corrected by 1-SMC? col color(s) of the catseyes. Defaults to blue. ... other parameters to pass to the plot function, e.g., typ="b" to draw lines, lty="dashed" to draw dashed lines Details Drawing the mean +/- a confidence interval is a frequently used function when reporting experimental results. By default, the confidence interval is 1.96 standard errors of the t-distribution. If within=TRUE, the error bars are corrected for the correlation with the other variables by reducing the variance by a factor of (1-smc). This allows for comparisons between variables. The error bars are normally calculated from the data using the describe function. If, alternatively, a matrix of statistics is provided with column headings of values, means, and se, then those values will be used for the plot (using the stats option). However, in this case, the error bars will be one s.e. rather than a function of the alpha level. I