Matlab Box Plot With Error Bars
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Search All Support Resources Support Documentation MathWorks Search MathWorks.com MathWorks Documentation Support Documentation Toggle navigation Trial Software Product Updates horizontal error bars matlab Documentation Home Statistics and Machine Learning Toolbox Examples Functions and Other errorbar matlab Reference Release Notes PDF Documentation Descriptive Statistics and Visualization Statistical Visualization Statistics and Machine Learning Toolbox
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Probability Distributions Exploration and Visualization Statistics and Machine Learning Toolbox Functions boxplot On this page Syntax Description Examples Create a Box Plot Create Box Plots for
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Grouped Data Create Notched Box Plots Create Compact Box Plots Input Arguments x g ax Name-Value Pair Arguments 'BoxStyle' 'Colors' 'MedianStyle' 'Notch' 'OutlierSize' 'PlotStyle' 'Symbol' 'Widths' 'ColorGroup' 'FactorDirection' 'FullFactors' 'FactorGap' 'FactorSeparator' 'GroupOrder' 'DataLim' 'ExtremeMode' 'Jitter' 'Whisker' 'Labels' 'LabelOrientation' 'LabelVerbosity' 'Orientation' 'Positions' More About Tips References See Also This is machine translation Translated by Mouse matlab errorbar color over text to see original. Click the button below to return to the English verison of the page. Back to English × Translate This Page Select Language Bulgarian Catalan Chinese Simplified Chinese Traditional Czech Danish Dutch English Estonian Finnish French German Greek Haitian Creole Hindi Hmong Daw Hungarian Indonesian Italian Japanese Korean Latvian Lithuanian Malay Maltese Norwegian Polish Portuguese Romanian Russian Slovak Slovenian Spanish Swedish Thai Turkish Ukrainian Vietnamese Welsh MathWorks Machine Translation The automated translation of this page is provided by a general purpose third party translator tool. MathWorks does not warrant, and disclaims all liability for, the accuracy, suitability, or fitness for purpose of the translation. Translate boxplotBox plotcollapse all in page Syntaxboxplot(x) exampleboxplot(x,g) exampleboxplot(ax,___)boxplot(___,Name,Value) exampleDescription exampleboxplot( and collaborate at raacampbell/notBoxPlot Note: Information from GitHub is updated daily. GitHub Highlights Issues1 Branches3 Contributors2 Download apps, toolboxes, and other File Exchange content using Add-On Explorer in MATLAB. » Watch video Highlights from notBoxPlot NBP.SEM_calc(vect, CI)SEM_calc - standard error of the mean, confidence standard error matlab interval NBP.examplePretty example use of notBoxPlot NBP.tInterval_Calc(vect, CI)tInterval_Calc - confidence interval based on the t-distribution notBoxPlot(y,x,varargin)notBoxPlot - Doesn't plot how to calculate error bars box plots! run_testsrun all unit tests for settings handler core_tests View all files Join the 15-year community celebration. Play games and win prizes! » Learn more 4.80952 4.8 | 23 ratings https://www.mathworks.com/help/stats/boxplot.html Rate this file 113 Downloads (last 30 days) File Size: 147 KB File ID: #26508 Version: 1.22 notBoxPlot by Rob Campbell Rob Campbell (view profile) 13 files 631 downloads 4.78681 28 Jan 2010 (Updated 12 Oct 2016) This function visualizes raw (grouped) data along with the mean, 95% confidence interval, and 1 SD. | Watch this File File Information Description Whilst box plots https://www.mathworks.com/matlabcentral/fileexchange/26508-notboxplot have their place, it's sometimes nicer to see all the data, rather than hiding them with summary statistics such as the inter-quartile range. This function (with a tongue in cheek name) addresses this problem. The use of the mean instead of the median and the SEM and SD instead of quartiles and whiskers are deliberate. Jittered raw data are plotted for each group. Also shown are the mean, and 95% confidence intervals for the mean. This plotting style is designed to be used alongside parametric tests such as ANOVA and the t-test. Comparing the jittered data to the error bars provides a visual indication of whether the normality assumptions of the statistical tests are being violated. Furthermore, it allows one to eyeball the data to look for significant differences between means (non-overlapping confidence intervals indicate a significant difference at the chosen p-value, which here is 5%). Also see: http://jcb.rupress.org/cgi/content/abstract/177/1/7 Finally, 1 SD is also shown. Note that if data are not normally distributed then these statistics will be less meaningful. The function has several examples and there are various visualization possibilities in addition to those shown in t Support Support Newsreader MathWorks Search MathWorks.com MathWorks Newsreader Support MATLAB Newsgroup MATLAB Central Community Home MATLAB Answers File Exchange Cody Blogs Newsreader Link Exchange ThingSpeak Anniversary Home Post A New Message Advanced Search Help MATLAB Central https://www.mathworks.com/matlabcentral/newsreader/view_thread/16510 Community Home MATLAB Answers File Exchange Cody Blogs Newsreader Link Exchange ThingSpeak Anniversary Home Post A New Message Advanced Search Help Trial software bar chart with error bars Subject: bar chart with error bars From: http://www.matlab-cookbook.com/recipes/0100_Statistics/029_boxplot_barchart.html Kevin Murphy Date: 8 May, 2000 18:39:14 Message: 1 of 13 Reply to this message Add author to My Watch List View original format Flag as spam Does anyone know how to add error error bar bars to a bar chart? Kevin Subject: bar chart with error bars From: John Williams Date: 9 May, 2000 12:04:40 Message: 2 of 13 Reply to this message Add author to My Watch List View original format Flag as spam Kevin Murphy wrote: > > Does anyone know how to add error bars to a bar chart? with the ERRORBAR command perhaps? or are you looking for something different to matlab box plot what that provides? Still, it should give you a starting point. John Subject: bar chart with error bars From: Kevin Murphy Date: 8 May, 2000 19:59:14 Message: 3 of 13 Reply to this message Add author to My Watch List View original format Flag as spam I call 'bar' on a matrix, so it gives me clusters of vertical bars like this * * * ** * ** ** I want to superimpose vertical error bars on these... Subject: bar chart with error bars From: John Williams Date: 9 May, 2000 16:14:08 Message: 4 of 13 Reply to this message Add author to My Watch List View original format Flag as spam Kevin Murphy wrote: > > I call 'bar' on a matrix, so it gives me clusters of vertical bars like > this > > * > * * > ** * > ** ** > > I want to superimpose vertical error bars on these... You already know the upper/lower error bounds, and just want to draw them on the graph? I don't know the exact answer off the top of my head, but I think you would get some good ideas by looking at the file errorbar.m Have you searched the user-contributed files and "solut a small number of groups, all of these plotting options are valid. Which to choose? Let's take a data set, plot it a bunch of different ways, and see how much information we glean from these three different plotting styles. First of all, a bar-chart with error bars being 95% confidence intervals for the mean: What story does that plot convey? It tells us we have 3 groups of data with means between about 2.0 and 2.5. The confidence in the mean is not great given the absolute value of the mean. i.e. the error bars look fairly large. The error bars across the three groups are pretty similar, with B being the smallest and C the largest. It doesn't look like there are any significant differences between the three groups. Ok, so now lets plot the same data but as a box plot and compare them. Wow! Now we're seeing a very different story. The large error bar in C is obviously due only to the huge outlier with a value of just under 7. Otherwise the data in C are tightly packed around the mean, so in reality it should have the smallest error bar of the three groups. The whiskers of the box plots of A and B indicate that the range of the data in those two distributions are similar. However, the blue boxes, which demarcate the region over which half the data can be found, look really different between A and B. That suggests something odd is going on, but we can't see what that is. Let's explore the data further by using a plotting style that overlays the raw data (the code can be found here): In this plot, the red lines represent the mean, the pink region the 95% confidence interval for the mean, and the blue region 1 standard deviation. At last, all is clear! Group A is actually bi-modal and not at all normally distributed. Consequently the standard error of the mean is a useless statistic for it and something is obviously "wrong" with those data. We also confirm that there is a nice, tight, distribution of data points in C. Finally, with the raw data present, its obvious what sort of sample size we're dealing with, which really helps to put the data into context. Discussion So which plot style is right? The answer, it seems, is that it doesn't matter all that much if you plot a box plot or a bar chart. But what does matter is that you take the time to overlay x
) creates a box plot of the data in x. If x is a vector, boxplot plots one box. If x is a matrix, boxplot plots one box for each column of x. exampleboxplot(Error Bar Standard Deviation