Bar Plot Error Bars
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error, or uncertainty in a reported measurement. They give a general idea of how precise a measurement is, or conversely, how far bar plot error bars matlab from the reported value the true (error free) value might be. Error
Bar Plot Error Bars R
bars often represent one standard deviation of uncertainty, one standard error, or a certain confidence interval (e.g., a 95% barplot with error bars matlab interval). These quantities are not the same and so the measure selected should be stated explicitly in the graph or supporting text. Error bars can be used to compare visually error bar in r two quantities if various other conditions hold. This can determine whether differences are statistically significant. Error bars can also suggest goodness of fit of a given function, i.e., how well the function describes the data. Scientific papers in the experimental sciences are expected to include error bars on all graphs, though the practice differs somewhat between sciences, and each journal will
Bar Graph With Error Bars Excel
have its own house style. It has also been shown that error bars can be used as a direct manipulation interface for controlling probabilistic algorithms for approximate computation.[1] Error bars can also be expressed in a plus-minus sign (±), plus the upper limit of the error and minus the lower limit of the error.[2] See also[edit] Box plot Confidence interval Graphs Model selection Significant figures References[edit] ^ Sarkar, A; Blackwell, A; Jamnik, M; Spott, M (2015). "Interaction with uncertainty in visualisations" (PDF). 17th Eurographics/IEEE VGTC Conference on Visualization, 2015. doi:10.2312/eurovisshort.20151138. ^ Brown, George W. (1982), "Standard Deviation, Standard Error: Which 'Standard' Should We Use?", American Journal of Diseases of Children, 136 (10): 937–941, doi:10.1001/archpedi.1982.03970460067015. This statistics-related article is a stub. You can help Wikipedia by expanding it. v t e Retrieved from "https://en.wikipedia.org/w/index.php?title=Error_bar&oldid=724045548" Categories: Statistical charts and diagramsStatistics stubsHidden categories: All stub articles Navigation menu Personal tools Not logged inTalkContributionsCreate accountLog in Namespaces Article Talk Variants Views Read Edit View history More Search Navigation Main pageContentsFeatured contentCurrent eventsRandom articleDonate to WikipediaWikipedia store Interaction HelpAbout WikipediaCommunity portalRecent changesContact page Tools What links hereR
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Calculate Standard Error In R
R One common frustration that I have heard expressed about R is that there is no automatic way to plot error bars (whiskers really) on bar plots. I just encountered this issue https://en.wikipedia.org/wiki/Error_bar revising a paper for submission and figured I'd share my code. The following simple function will plot reasonable error bars on a bar plot. PLAIN TEXT R: error.bar <- function(x, y, upper, lower=upper, length=0.1,...){ if(length(x) != length(y) | length(y) !=length(lower) | length(lower) != length(upper)) stop("vectors must be same length") arrows(x,y+upper, x, y-lower, angle=90, code=3, length=length, ...) } Now let's use it. First, I'll create 5 http://monkeysuncle.stanford.edu/?p=485 means drawn from a Gaussian random variable with unit mean and variance. I want to point out another mild annoyance with the way that R handles bar plots, and how to fix it. By default, barplot() suppresses the X-axis. Not sure why. If you want the axis to show up with the same line style as the Y-axis, include the argument axis.lty=1, as below. By creating an object to hold your bar plot, you capture the midpoints of the bars along the abscissa that can later be used to plot the error bars. PLAIN TEXT R: y <- rnorm(500, mean=1) y <- matrix(y,100,5) y.means <- apply(y,2,mean) y.sd <- apply(y,2,sd) barx <- barplot(y.means, names.arg=1:5,ylim=c(0,1.5), col="blue", axis.lty=1, xlab="Replicates", ylab="Value (arbitrary units)") error.bar(barx,y.means, 1.96*y.sd/10) Now let's say we want to create the very common plot in reporting the results of scientific experiments: adjacent bars representing the treatment and the control with 95% confidence intervals on the estimates of the means. The trick here is to create a 2 x n matrix of your bar values, where each row holds the values to be compared (e.g., treatment vs. control, male vs. female, etc.). Let's look at our same
bars? Say that you were looking at writing scores broken down by race and ses. You might want to graph the mean and confidence interval for each group using a bar chart with error bars as illustrated http://www.ats.ucla.edu/stat/stata/faq/barcap.htm below. This FAQ shows how you can make a graph like this, building it up step by step. First, lets get the data file we will be using. use http://www.ats.ucla.edu/stat/stata/notes/hsb2, clear Now, let's use the collapse command to make the mean and standard deviation by race and ses. collapse (mean) meanwrite= write (sd) sdwrite=write (count) n=write, by(race ses) Now, let's make the upper and lower values of the confidence interval. generate hiwrite = meanwrite + invttail(n-1,0.025)*(sdwrite / sqrt(n)) generate lowrite error bar = meanwrite - invttail(n-1,0.025)*(sdwrite / sqrt(n)) Now we are ready to make a bar graph of the data The graph bar command makes a pretty good bar graph. graph bar meanwrite, over(race) over(ses) We can make the graph look a bit prettier by adding the asyvars option as shown below. graph bar meanwrite, over(race) over(ses) asyvars But, this graph does not have the error bars in it. Unfortunately, as nice as the graph bar command is, it does not bar plot error permit error bars. However, we can make a twoway graph that has error bars as shown below. Unfortunately, this graph is not as attractive as the graph from graph bar. graph twoway (bar meanwrite race) (rcap hiwrite lowrite race), by(ses) So, we have a conundrum. The graph bar command will make a lovely bar graph, but will not support error bars. The twoway bar command makes lovely error bars, but it does not resemble the nice graph that we liked from the graph bar command. However, we can finesse the twoway bar command to make a graph that resembles the graph bar command and then combine that with error bars. Here is a step by step process.First, we will make a variable sesrace that will be a single variable that contains the ses and race information. Note how sesrace has a gap between the levels of ses (at 5 and 10). generate sesrace = race if ses == 1 replace sesrace = race+5 if ses == 2 replace sesrace = race+10 if ses == 3 sort sesrace list sesrace ses race, sepby(ses) +---------------------------------+ | sesrace ses race | |---------------------------------| 1. | 1 low hispanic | 2. | 2 low asian | 3. | 3 low african-amer | 4. | 4 low white | |---------------------------------| 5. | 6 middle hispanic | 6. | 7 middle asian | 7. | 8 middle african-amer | 8. | 9 middle white