Qqplot In R

It is a generic function, meaning, it has many methods which are called according to the type of object passed to plot(). Introduction to normality tests A normality test is a statistical process used to determine if a sample or any group of […]. Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. You simply give the sample you want to plot as a first argument. This function is similar to, but more general than, qqplot, qqnorm, qqline. Hello! SORRY PROBLEMS WITH FUNCTIONS AGAIN I NEED TO RUN A qqPlot I TRIED TO INSTALL IT , BUT A WARNING MESSAGE SAID qqPlot is not available for. • The first two arguments to qqplot are the samples of values to be compared. Any distribution for which quantile and density functions exist in R (with prefixes q and d, respectively) may be used. # FILENAME IS Chap2RCode. If we handed the plot function only one vector, the x-axis would consist of sequential integers. A QQ plot is a graphical technique for determining if two data sets come from populations with a common distribution. The qqPlot function is a modified version of the R functions qqnorm and qqplot. R Programming. It plots sorted data values (quantiles of the empirical distribution) against the corresponding quantiles of a theoretical distribution (here the normal distribution). There are several methods of fitting distributions in R. CMplot:一个R包,画曼哈顿图的。 q-q plot:分位数-分位数图,assess if a set of data plausibly came from some theoretical distribution such as a Normal or exponential. While I'm still at early chapters, I've learned a lot already. This particular type of Q Q plot is called a normal quantile-quantile (QQ) plot. Q-Q plot is used to compare two distributions. Sometimes confusion arises, when the software packages produce different results. This is often used to check whether a sample follows a normal distribution, to check whether two samples are drawn from the same distribution. The most used plotting function in R programming is the plot() function. R Quantile-Quantile Plot Example Quantile-Quantile plot is a popular method to display data by plot the quantiles of the values against the corresponding quantiles of the normal (bell shapes). Data scientists and statisticians are often faced with this problem: they have some observations of a quantitative character x 1, x 2, …, x n and they wish to test if those observations, being a sample of an unknown population, belonging to a. qqplot produces a QQ plot of two datasets. The following are code examples for showing how to use statsmodels. Otherwise, the variables can be any numeric variables in the input data set. This QQ plot is constructed by plotting the sample generated from Frechet simulation (we will name it MaxstarF) compared to the Weibull distribution. It's basically the spread of a dataset. I tend to prefer ggplot, both because they're easier to manipulate and I find them more aesthetically pleasing. In statistics, a QQ Plot ("Q" stands for Quantile) creates a graphical comparison between two distributions by plotting their quantiles against each other. The confidence band is added using the polygon() function. Options in QQPLOT statement specify the theoretical distribution for the plot or add features to the plot. Specifying an arbitrary distribution for your probability scale. 3 Gráficos cuantil cuantil. You can see that green is roughly normally distributed, except that on the left hand side. We use cookies for various purposes including analytics. Interpretation. This is the qq-plot. qq-Plot function in version 3. Fitting distributions consists of finding a mathematical function which represents a statistical variable. In light of my recent studies/presenting on The Mechanics of Data Visualization, based on the work of Stephen Few (2012); Few (2009), I realized I was remiss in explaining the ordering of variables from largest to smallest bar. Provides complete documentation of the Base SAS statistical procedures (CORR, FREQ, and UNIVARIATE), including introductory examples, syntax, computational details, and advanced examples. First, try the examples in the sections following the table. Data scientists and statisticians are often faced with this problem: they have some observations of a quantitative character x 1, x 2, …, x n and they wish to test if those observations, being a sample of an unknown population, belonging to a. The empirical quantiles are plotted against the quantiles of a standard normal distribution. qqplot against theoretical quantiles. Graphical parameters may be given as arguments to qqnorm, qqplot and qqline. A comparison line is drawn on the plot either through the quartiles of the two distributions, or by robust regression. QQ plots is used to check whether a given data follows normal distribution. statsmodels actually has a qqplot method that we can use directly, but it's not very customizable, hence this two-step approach. The residual data of the simple linear regression model is the difference between the observed data of the dependent variable y and the fitted values ŷ. We recommend you read our Getting Started guide for the latest. It is assumed that you know how to enter data or read data files which is covered in the first chapter, and it is assumed that you are familiar with the different data types. Quantiles & boxplots using R. We then need to convert this list object to a dataframe using as. fitted plots. The qqplotr package extends some ggplot2 functionalities by permitting the drawing of both quantile-quantile (Q-Q) and probability-probability (P-P) points, lines, and confidence bands. happy holidays!--. Leave the first row blank for labeling the columns. This is often used to check whether a sample follows a normal distribution, to check whether two samples are drawn from the same distribution. In R, you add lines to a plot in a very similar way to adding points, except that you use the lines() function to achieve this. To draw the qqplot of a vector u in R, you simply type qqnorm(u): Figure 1(c) contains the qq-plot of the exam data we have been studying here. I have a bunch of p values from fisher's exact test. As part of the type 2 diabetes whole-genome scan, we developed scripts (written in R) to generate quantile-quantile (Q-Q) plots as well plots of the association results within their genomic context (gene annotations and local linkage disequilibrium patterns). Quantile-Quantile Plots Description. However, in most other systems, such as R, normal Q-Q plot is available as a convenience feature, so you don't have to work so hard!. aweights and fweights are allowed; see [U] 11. chisq() which will provide a QQ plot including a grey confidence band. Plot histogram or QQ-plot of all p-values. The points are not clustered on the 45 degree line, and in fact follow a curve, suggesting that the sample data is not normally distributed. Quantiles & boxplots using R. More Public Member Functions inherited from XYLineChart XYLineChart. I then -log10 transform these two vectors. I suggest using R unless there is a particular capability available only in Splus. Concept behind the mosaic plot: Let's consider the UCBAdmisssions data set. In the first example we simply hand the plot function two vectors. Here are some options. Function for SPSS-type QQ-plot. qqline adds a line to a normal quantile-quantile plot which passes through the first and third quartiles. probplot functions plot expected values versus actual data values for visualization of fit to a. R Commander QQ Plot with triangular distribution. R 언어_ 그래픽 : qqnorm(), qqline(), qqplot() : qqnorm : 정규분포의 QQ plot을 그리는 함수. The points plotted in a Q–Q plot are always non-decreasing when viewed from left to right. qqline adds a line to a “theoretical”, by default normal, quantile-quantile plot which passes through the probs quantiles, by default the first and third quartiles. "QQ" stands for Quantile-Quantile plot -- the point of these figures is to compare two probability distributions to see how well they match or where differences occur. The whole point of this demonstration was to pinpoint and explain the differences between a QQ-plot generated in R and SPSS, so it will no longer be a reason for confusion. This function is analogous to qqnorm for normal probability plots. The standard qqplot functions in R do not provide confidence intervals but the qq. These are good functions to use. Grouping can be represented by color, symbol, size, and transparency. Using car functions inside user functions. This function plots a QQplot as ggplot in R - Parts of the code copied from `car:::qqPlot` - gg_qq. Its popularity in the R community has exploded in recent years. This function plots QQplot for two empirical data sets. Sort the data in ascending order (look under the Data menu). R Plot PCH Symbols Chart Following is a chart of PCH symbols used in R plot. • A normal QQ plot graphs the quantiles of the data against. statsmodels actually has a qqplot method that we can use directly, but it's not very customizable, hence this two-step approach. A QQ plot is a graphical technique for determining if two data sets come from populations with a common distribution. Data Cleaning - How to remove outliers & duplicates. They are from open source Python projects. If it isn't suitable for your needs, you can copy and modify it. I built the above Q-Q plots using more rudimentary functions because. The components of the QQPLOT statement are as follows. QQplot The QQplot is used to examine whether or not the data are normally distributed (normal = bell curve). 776 Statistical Computing R: Graphics. qqplot(x) displays a quantile-quantile plot of the quantiles of the sample data x versus the theoretical quantile values from a normal distribution. The whole point of this demonstration was to pinpoint and explain the differences between a QQ-plot generated in R and SPSS, so it will no longer be a reason for confusion. If you specify a VAR statement, the variables must also be listed in the VAR statement. More QQPlot (String title, String XLabel, String YLabel, ContinuousDistribution dist, double[][] data, int r) Constructs a new QQPlot instance. qq plot interpretation SAS doc gives the references and a few simple rules, and R community gives more examples around these rules. In QQPLOT statement, you can specify the variables for which to create Q-Q plots. Using the default R interface (RGui, R. Quantile-Quantile Plots Description. Thus in the above example, the percentile for -. This function plots a QQplot as ggplot in R - Parts of the code copied from `car:::qqPlot` - gg_qq. When I create a QQ plot in R with the sample quantile on the Y axis and theoretical quantile on the X axis , I don't get why the theoretical axis is shown as -3 through to +3. • A normal QQ plot graphs the quantiles of the data against. Function for SPSS-type QQ-plot. Now we are ready to get things done in R. 3 Gráficos cuantil cuantil. Any distribution for which quantile and density functions exist in R (with prefixes q and d, respectively) may be used. They are from open source Python projects. Without having access to your dataset, it is not possible for me to say what's wrong, but probably qqPlot expects "norm" instead of "normal". qqplot and scipy. The function is mainly intended for teaching the concept of quantile plots. qqnorm is a generic function the default method of which produces a normal QQ plot of the values in y. qqnorm is a generic functions the default method of which produces a normal QQ plot of the values in y. R Documentation: Add Line Going Through the Quantiles of a Q-Q Plot Description. The QQ plot has the "S" shape indicating a bimodal distribution. Sign in Sign up Instantly share code, notes, and snippets. As a non-parametric alternative to paired t-tests, a permutation test can be used. How to compute the one sample t-test in R? A good practice before doing t-tests in R is to visualize the data thanks to a boxplot (or a density plot, or eventually both). The next function we look at is qnorm which is the inverse of pnorm. We recommend you read our Getting Started guide for the latest. The plot on the right is a normal probability plot of observations from an exponential distribution. qqplot(x) displays a quantile-quantile plot of the quantiles of the sample data x versus the theoretical quantile values from a normal distribution. The R base functions qqnorm () and qqplot () can be used to produce quantile-quantile plots: qqnorm (): produces a normal QQ plot of the variable. For example, if you have a normally distributed random variable with mean zero and standard deviation one, then if you give the function a probability it returns the associated Z-score:. Graphical parameters may be given as arguments to qqnorm, qqplot and qqline. They are from open source Python projects. plot() function in the car library does. See[R] regress postestimation diagnostic plots for regression diagnostic plots and[R] logistic postestimation for logistic regression diagnostic plots. For a given dataset, the results are slightly different. qqline adds a line to a “theoretical”, by default normal, quantile-quantile plot which passes through the probs quantiles, by default the first and third quartiles. First the data in both datasets is sorted. If you have a basic understanding of the R language, you’re ready to get started. To use qqplot, pass it two vectors that contain the samples that you want to compare. These options describe the visual properties of the axes, legends, panels, strips, and the overall plot. The idea behind qnorm is that you give it a probability, and it returns the number whose cumulative distribution matches the probability. For example, consider the trees data set that comes with R. Any distribution for which quantile and density functions exist in R (with prefixes q and d, respectively) may be used. qqnorm is a generic function the default method of which produces a normal QQ plot of the values in y. This is often used to check whether a sample follows a normal distribution, to check whether two samples are drawn from the same distribution. In most cases, you don’t want to compare two samples with each other, but compare a sample with a theoretical sample that comes from a certain distribution (for example, the normal distribution). car Companion to Applied Regression. We look at some of the ways R can display information graphically. R Quantile-Quantile Plot Example Quantile-Quantile plot is a popular method to display data by plot the quantiles of the values against the corresponding quantiles of the normal (bell shapes). As an analysis. It’s very easy to run: just use a plot() to an lm object after running an analysis. I wanted to use R's rudimentary functions to illustrate the 5 steps of creating a Q-Q plot. Generates a probability plot for a ,specified theoretical distributions, i. Description. This function plots your sample against a normal distribution. A comparison line is drawn on the plot either through the quartiles of the two distributions, or by robust regression. In the first example we simply hand the plot function two vectors. In the Stats I course for psychology freshman at Bremen University (Germany), we teach two software packages, R and SPSS. These options describe the visual properties of the axes, legends, panels, strips, and the overall plot. R Documentation: Add Line Going Through the Quantiles of a Q-Q Plot Description. array(inter_ex),'expon') Inter_ex is an array containing the sample I would like to check the exponential distribution against. Testing normality should be performed on the day differences using a Shapiro-Wilk normality test (or equivalent), and/or a QQ plot for large sample sizes. You plot one quantile against another and you see if their coordinate pairs form a straight line. The next function we look at is qnorm which is the inverse of pnorm. qqplot against theoretical quantiles. You can use any number of QQPLOT statements in the UNIVARIATE procedure. In summary: percentile = r/(N+1). Online Scatter Plot Generator. Normal Probability Plot of Data From an Exponential Distribution. The idea behind qnorm is that you give it a probability, and it returns the number whose cumulative distribution matches the probability. The EnvStats function qqPlot allows the user to specify a number of different distributions in addition to the normal distribution, and to optionally estimate the distribution parameters of the fitted distribution. Give data as an input to qqnorm() function. qqplot produces a QQ plot of two datasets. About 62% (R-squared = 0. Using car functions inside user functions. It looks like you're trying to grab summary functions from each entry in a list, ignoring the elements set to -999. qqnorm(x, datax=T) # uses Blom's method by default qqline(x, datax=T) There are some obvious differences: The most obvious one is that the R plot seems to contain more data points than the SPSS plot. Sign in Sign up. Keywords: R, qq plot, q-q plot, qqnorm, confidence intervals Last modified 4/2/06. Recently, as a part of my Summer of Data Science 2017 challenge, I took up the task of reading Introduction to Statistical Learning cover-to-cover, including all labs and exercises, and converting the R labs and exercises into Python. ggplot2 is a data visualization package for the statistical programming language R. This one shows how. GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. • A normal QQ plot graphs the quantiles of the data against. In the first example we simply hand the plot function two vectors. R Lattice Graphics. Summary: If the QQ-plot has the vast majority of points on or very near the line, the residuals may be normally distributed. Prior to performing a paired t-test, it is important to validate our assumptions to ensure that we are performing an appropriate and reliable comparison. The next function we look at is qnorm which is the inverse of pnorm. We can interpret the graphic as follows:. I built the above Q-Q plots using more rudimentary functions because. Provides complete documentation of the Base SAS statistical procedures (CORR, FREQ, and UNIVARIATE), including introductory examples, syntax, computational details, and advanced examples. Type 'demo()' for some demos, 'help()' for on-line help, or 'help. The R Inferno, Burns, Patrick, 2011 , "If you are using R and you think you're in hell, this is a map for you. To remind you of the discussion, the question was about the discrepancy between qqnorm in base R and stat="qq" in ggplot2. The plot is convex. qqplot and scipy. The function stat_qq() or qplot() can be used. This method plots a histogram or QQ-plot of p-valuesfor all tests performed by Matrix_eQTL_engine. Example 4: Create QQplot with ggplot2 Package. Q-Q plot Problem. In the case of the latter, both inputs will be converted to ProbPlot instances using only the default values - so use. Quantile-Quantile Plots Description. These are good functions to use. Home › Sample code › Chapter 15 – Testing Differences and Relations. The following are code examples for showing how to use statsmodels. 69 lines (58 sloc) 2. 953 and thus very good and better than the r 2 from the linear regression. Here is the help of the function qqplot I used. The graph looks like this: I need to blow up the x and y axis to look at how close they are to the. A video tutorial for creating QQ-plots in R. Description. # Overriding the default grouping # The plot has a discrete scale but you want to draw lines that connect across # groups. qqplot and scipy. Assessing the fit of a specific distribution for given data can be done via probability plots ppPlot and quantile-quantile plots qqPlot, as well as formal test methods like the Anderson Darling Test (citep{Stephens. For quite a while I worked with histograms, which are useful for seeing the spread of the data, as well as how closely it resembles a normal dataset. To use qqplot, pass it two vectors that contain the samples that you want to compare. Quantile-Quantile Plots Description. Here are some options. Report basic summary statistics by a grouping variable. We illustrate the use of the QQ Plot data analysis tool in the following example. org [mailto:r-help-bounces at r-project. GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. This is accomplished by binding plot inputs to custom controls rather than static hard-coded values. Histograms leave much to the interpretation of the viewer. Fitting distributions consists of finding a mathematical function which represents a statistical variable. qqplot produces a QQ plot of two datasets. [转载]R QQ plot_ccpacer_新浪博客,ccpacer, QQPlot用于直观验证一组数据是否来自某个分布,或者验证某两组数据是否来自同一(族)分布。. Put the data below in a file called data. R Lattice Graphics. Part II: Deploying a Dash Application to Operationalize Machine Learning Models; Part I: Operationalizing R models with Dash Enterprise and Microsoft Azure;. Plotting Genome-Wide Association Results The interpretation of genome-wide association results can be greatly facilitated by visualization. The EnvStats function qqPlot allows the user to specify a number of different distributions in addition to the normal distribution, and to optionally estimate the distribution parameters of the fitted distribution. Draws theoretical quantile-comparison plots for variables and for studentized residuals from a linear model. Hans Bühlmann on the Occasion of his 90th Birthday. ### Using a QQ plot to check for. Emulating R plots in Python Jul 11, 2017 6 minute read For this, I'm using ProbPlot and its qqplot method from statsmodels graphics API. Data Cleaning - How to remove outliers & duplicates. Note that, as with Choropleth mapping, the # of bins makes a difference in one's interpretation. 2 Making orthogonal basis # n = 2 y1 = c(0,1/sqrt(2)) x1 = c(0,1/sqrt(2)) x2 = c(0,-1/sqrt(2)) y2 = c(0,1/sqrt(2. Plot is divided into rectangles. a <- seq(1, 250, 1) 利用qqnorm函数直接绘制出了如下正态检验qq图. You will need to change the command depending on where you have saved the file. The quick fix is meant to expose you to basic R time series capabilities and is rated fun for people ages 8 to 80. 3D Scatter Plots in R How to make interactive 3D scatter plots in R. Linear interpolation. A complete example of plotting the test dataset as a QQ plot is provided below. Here's a function to create such a plot with. The trick here is to manage the pch and cex arguments in the plot function. R 언어_ 그래픽 : qqnorm(), qqline(), qqplot() : qqnorm : 정규분포의 QQ plot을 그리는 함수. In R, you add lines to a plot in a very similar way to adding points, except that you use the lines() function to achieve this. SET THE FOLLOWING IQ SCORES INTO COLUMN C1 (data come here) NSCORES FOR DATA IN COL C1, PUT IN COL C2 PLOT COL C1 VS COL C2 (PROBABILITY PLOT) CORRELATION BETWEEN C1 AND C2 (R-SUB-P) STOP. Since R runs on so many different operating systems, and supports so many different graphics formats, it's not surprising that there are a variety of ways of saving your plots, depending on what operating system you are using, what you plan to do with the graph, and whether you. This particular type of Q Q plot is called a normal quantile-quantile (QQ) plot. That will be your y-axis values. R defines the following functions: qqPlot. Here is a histogram of 2016 county total votes for third party presidential candidates. Check that it works by simulating from a t-df and making a QQplot. R is free and open source and you can view the source, report issues or contribute on GitHub. The standard qqplot functions in R do not provide confidence intervals but the qq. ggplot2 can serve as a replacement for the base graphics in R and contains a number of. QQ Plots are a standard visualization that compares the distribution of your data under study to the normal distribution. Axes Labels. qqnorm produces a normal QQ plot of the values in y. • The function is called qqplot. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. The next function we look at is qnorm which is the inverse of pnorm. If the two sets come from a population with the same distribution, the points of the QQ plot should fall approximately along the reference line y = x. I tend to prefer ggplot, both because they're easier to manipulate and I find them more aesthetically pleasing. Report basic summary statistics by a grouping variable. There are several methods of fitting distributions in R. Interpretation. Adding color to the aesthetics will prompt plotnine to display a two-dimensional plot using displ (engine displacement, in liters) on its x- and hwy (highway miles per gallon) on its y-axis and color the data according to the variable class. Concept behind the mosaic plot: Let's consider the UCBAdmisssions data set. If you're looking for a simple way to implement it in R, pick an example below. But generally, we pass in two vectors and a scatter plot of these points are plotted. Dans cette partie, nous montrons comment transformer des données en graphiques avec R, qu'il s'agisse de graphiques simples pour des données univariées ou bivariées, ou des graphiques dont la compréhension requiert un peu d'algèbre linéaire ou des algorithmes non triviaux. QQPlot图是用于直观验证一组数据是否来自某个分布,或者验证某两组数据是否来自同一(族)分布。在教学和软件中常用的是检验数据是否来自于正态分布。. qqplot r r However, all bets are off if you attempt to a qqplot of the residual, say with a variable like "length" in the auto dataset. The POT package aims to provide operational tools to analyze POT. Grouping can be represented by color, symbol, size, and transparency. This is a re-write of the QQ-plotting functions provided by stats, using the ggplot2 library. 622) of the variability in breast cancer rate is explained by income and alcohol consumption. This 'population structure', as it's called, is the most commonly discussed confounder, but many others exist, such as whether cases and controls were genotyped in the same laboratory, or the DNA was collected by the same method. " R courses at Coursera. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management. This function plots QQplot for two empirical data sets. Actually I'm working with python using the function qqplot from the package statsmodels. One of these situations occurs when the QQ-plot is. Workshop Overview. Actually they use the first and the third Quartiles Q1 and Q3. We could then use the qqplot() function to plot the observed data (sorted) against the theoretical quantiles of the standard normal. In this example, we show how to make a Stem and Leaf plot in R using the ChickWeight data set, which is provided by the R Studio. My sense is that more and more statisticians are moving to R, and that this will become the standard in future years, with packages being developed for R rather than for Splus. R 언어_ 그래픽 : qqnorm(), qqline(), qqplot() : qqnorm : 정규분포의 QQ plot을 그리는 함수. statsmodels. The function stat_qq() or qplot() can be used. The points plotted in a Q-Q plot are always non-decreasing when viewed from left to right. The Q-Q Plot Purpose In this assignment you will learn how to correctly do a Q-Q plot in Microsoft Excel. For example, the median of a dataset is the half-way point. 6 different insect sprays (1 Independent Variable with 6 levels) were tested to see if there was a difference in the number of insects. qqplot produces a QQ plot of two datasets. The functions of this package also allow a detrend adjustment of the plots, proposed by Thode (2002) to help reduce visual bias when assessing. If you require to import data from external files then, I suggest you to refer R Read CSV article to understand the importing of the CSV file. If the points in a Q-Q plot appear to fall on a straight line, that is evidence that the data can be approximately modeled by the target distribution. Create a Stem and Leaf Plot in R Programming. qq-plot is short for quantile-by-quantile plot. Control Chart - Create an X-bar, R or S Chart for process control. For a comprehensive view of probability plotting in R, see Vincent Zonekynd's Probability Distributions. One of the quantiles is your sample observations placed in ascending order. In general, studentized residuals are going to be more effective for detecting outlying Y observations than standardized residuals. For a given dataset, the results are slightly different. It is particularly easy to use for simple plots. Unfortunately, since we are not comparing to any theoretical distribution in this case, there is nothing comparable to qqline( ) available in qqplot. Options in QQPLOT statement specify the theoretical distribution for the plot or add features to the plot. On the right you can see the Q-Q plot that is drawn with the same data that is displayed in the histogram. Paired t-tests can be conducted with the t. Various implementations of Q-Q plots exist in R. As you can see based on Figure 3, our two input data sets do now follow the same distribution, since the QQplot is not following a straight line. To my knowledge, there is no function by default in R that computes the standard deviation or variance for a population. For example, you take the height of 30 people and place them in order from smallest to largest. Depending on what you said in the installation process, you might also have icons on your desktop. Plotly Fundamentals. The Correlation Coefficient of the QQ-Plot In its complete form, the R-command qqnorm has the following syntax: qqnorm(u;datax = FALSE;plot = TRUE):. A video tutorial for creating QQ-plots in R. and converting the R labs and exercises into Python. In R (or otherwise) write QQplot for t-distribution with 2df. probplot axis labeling. This method plots a histogram or QQ-plot of p-valuesfor all tests performed by Matrix_eQTL_engine. Stine Department of Statistics The Wharton School of the University of Pennsylvania Philadelphia, PA 19104-6340 September 9, 2016 Abstract A normal quantile-quantile (QQ) plot is an important diagnostic for checking the as-sumption of normality. Normal Probability Plot This video shows how to create a normal probability plot using spreadsheet tools that you probably have laying around the house. Assessing the fit of a specific distribution for given data can be done via probability plots ppPlot and quantile-quantile plots qqPlot, as well as formal test methods like the Anderson Darling Test (citep{Stephens. Type 'demo()' for some demos, 'help()' for on-line help, or 'help. The QQ plot The quantile-quantile plot, or QQplot, is a simple graphical method for comparing two sets of sample quantiles. Linear Regression Plots: How to Read a QQ-Plot. [转载]R QQ plot_ccpacer_新浪博客,ccpacer, QQPlot用于直观验证一组数据是否来自某个分布,或者验证某两组数据是否来自同一(族)分布。.