" /> Runif In R Example

# Runif In R Example

Aggregate is a function in base R which can, as the name suggests, aggregate the inputted data. Loop, Condition Statements. There is a R package that does boostrapping, called boot. See the help of RNGkind() to learn about random number generators. This was part of a graduate thesis in which I also proposed de novo spatial modeling parameters to account for the lateral mosaic nature of the seafloor using the R programming interface. A minimal network example in R May 18, 2012 Network science is potentially useful for certain problems in data analysis, and I know close to nothing about it. A simple optimization problem is solved from scratch using R. 1 Description Provides functions to perform. Unfortunately, base graphics only offers a built in plot type for normal qq plots. A step by step guide on how Genetic Algorithm works is presented in this article. Overview of random number generation in R R [https://cran. Navigation. Snow relies on the Master/Slave model of communcation: One device (master) controls one or more other devices (slaves). The table function counts the number of occurences. Another resource is the StatSoftEquivs wiki. sample<-runif(10, min=0,. The table function counts the number of occurences. SD, 1:2), by=id] would lag every column of. The first example uses a uniform (rectangular) distribution. To generate an IID sample from a given distribution in R, we can use the family of functions r{name of the distribution}. Rakhshan and H. io Find an R package R language docs Run R in your browser R Notebooks randtoolbox Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests. The readinteger function has been explained in a previous example. For example, for the Naive portfolio (black dot), the maximum return for that level of risk is about 0. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to. The round function rounds the first argument to the specified number of digits. There are no built-in R functions for dealing with this distribution, but because it is an extremely simple distribution it is easy to write such functions. 2 Patterns 1. Then, make a histogram of the distance from the origin: p X2 + Y2. Estimate transformations of x and y such that the regression of y on x is approximately linear with constant variance. For example if you want a smooth for 3 covariates made up of a tensor product of a 2 dimensional t. These functions set or modify the current random number state and are implemented as "user-defined" random number generators. At first sight, you’d think it replicates the value of an expression the desired number of times, and sticks the result in a vector, like this: That would be somewhat useful if you wanted to create vectors with a fixed number of equal elements, although you would be better off using the rep function for that instead:. Then, make a histogram of the distance from the origin: p X2 + Y2. The focus of the first section is on graphing continuous data. dunif gives the density, punif gives the distribution function, qunif gives the quantile function, and runif generates random deviates. There are two examples in this report. R plotting command are output at a very low level as TikZ commands. Often, you want to make choices and take action dependent on a certain value. When sharing results with colleagues, it might be useful to compact everything in a single file. This tutorial explains the usage of WHICH function in R and how it works with examples. That was a lie. The initialization used in R generates the initial state in a way, which leaves linear dependencies mod 2 among the bits in the initial state. This example demonstrates randomly partitioning data into training and testing sets. In R Programming language, recycling of elements is when we perform operations on two different vectors having different lengths. To generate numbers from a normal distribution, use rnorm(). This example generates one uniform random number:. The first line generates a list of random numbers. Refresh to get latest versions. For example, for the Naive portfolio (black dot), the maximum return for that level of risk is about 0. I use examples from Paul Nahin’s book, Digital Dice: Computational Solutions to Practical Probability Problems, and I show how his MATLAB code differs from what is possible in R. One can simulate random numbers from uniform distributions in R using runif function. For example if you have the function parsefile. Where does the data come from, in the first place? If you are being asked or are asking yourself, genuine questions, about real-world problems, you probably already have your data. hat - mean(exp(-x)) print(theta. We have provided working source code on all these examples listed below. SD, 1:2), by=id] would lag every column of. This I do for each asset class i. sample<-runif(10, min=0,. Tidy data is data that's easy to work with: it's easy to munge (with dplyr), visualise (with ggplot2 or ggvis) and model (with R's hundreds of modelling packages). Generate a random number between 5. The focus of the first section is on graphing continuous data. When sharing results with colleagues, it might be useful to compact everything in a single file. The model needs to know what input shape it should expect. Estimate transformations of x and y such that the regression of y on x is approximately linear with constant variance. As a language for statistical analysis, R has a comprehensive library of functions for generating random numbers from various statistical distributions. R floor Function Example 3. We use cookies to ensure that we give you the best experience on our website. However if we are not careful, it's very easy to write programs that are incredibly slow. Likewise, raster data could be represented by a matrix or higher-order array. 3d density plot. 5,0) # rounds to even number [1] 22 > round(3. 8: Add function inter. This I do for each asset class i. As with most R packages, beeswarm can be obtained from CRAN, or can can be downloaded and installed automatically by entering the following line at the R prompt:. How To Create a. simply provides returns R code that tells the user that function is specified but does not actual evaluate (or "instantiate") the function. There are 3 different ways in which data can be imported in R language-. As far as I am aware, the fitted glm object doesn't directly give you any of the pseudo R squared values, but McFadden's measure can be readily calculated. Since Mersenne Twister performs only operations, which are linear mod 2, these dependencies propagate to the output sequence. Date()" output: rmarkdown::html_document: toc: true toc_float: true toc_depth: 4 number_sections: true theme: "flatly" highlight: "textmate" css: "sevenbridges. md ├── report │ └── report. , multilayer feedforward perceptron, supervised ANN, etc. This is great for exploration, because you can do anything in your interactive plot you can do in R, but it’s not so great for publication. It let’s you specify variance-covariance structures for the residuals and is well suited for repeated measure or longitudinal designs. In it, the elements of the shorter length vector are used to complete the operation. Estimate transformations of x and y such that the regression of y on x is approximately linear with constant variance. If the provided name is a valid R color, is_color() should return TRUE. SAS PROC MCMC example in R: Logistic Regression Random-Effects Model In this post I will run SAS example Logistic Regression Random-Effects Model in four R based solutions; Jags, STAN, MCMCpack and LaplacesDemon. 11 (page 32). I am moving 100 "particles" in both x,y dimensions and would like to plot the. The R Function of the Day series will focus on describing in plain language how certain R functions work, focusing on simple examples that you can apply to gain insight into your own data. dunif gives the density, punif gives the distribution function qunif gives the quantile function and runif generates random deviates. There are no built-in R functions for dealing with this distribution, but because it is an extremely simple distribution it is easy to write such functions. Explain basic R concepts, and illustrate with statistics textbook homework exercise. The recently released version 3. The random value can be forced to obey certain statistical assumptions, which in this example will be a triangular distribution. io Find an R package R language docs Run R in your browser R Notebooks randtoolbox Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests. Though the above is purposely not a good example, Mapbox is capable of stunning customized cartography, which is available to R users in their cartography projects, Shiny applications, etc. Topics in statistical data analysis will provide working examples. Syntax for set. Here I will demonstrate how to customize legends and arrange to the circular plot. 1 Getting a random number. The first line generates a list of random numbers. function (n, min = 0 , max = 1 ). You should use R's dpois function. Now let's find the impact of the number of trials on the mean and absolute difference from the theoretical probabilities w. It let’s you specify variance-covariance structures for the residuals and is well suited for repeated measure or longitudinal designs. The stock price example confuses me. One example is where y = a + b*w + for fixed weights 'w' and where (a, b) are bivariate Normals, where (a_i, b_i) is bivariate Normal and all 2-vectors are independent. In this case one may follow three different ways: (i) try to linearize the […]. 19709386) is the ninth element. The models have been tested and run without additional data in R. R Sample is useful for selecting a sample from a finite set of items. runif, rbinom, rnorm. However, if you require a custom implementation, you can use rxExec to manually construct and manage a distributed workload. Here are examples of the most common ones. 2 posts published by Claudia Vitolo during July 2013. sir how i can compare 10 random locations(set no 1) with other 4 random locations(set no 2) having xy coordinates of both sets keeping in mind one restriction that comparison or matching is done only if set 1 locations enroute set 2 locations or otherwise kindly help i mean wat function i can use for this problem in R no such code is available as yet is there any literature available in R for. As illustrated in the example above, this is done by passing an input_shape argument to the first layer. The table below gives the names of the functions for each distribution and a link to the on-line documentation that is the authoritative reference for how the functions are used. 5 percentage points higher than the portfolio. Likewise, raster data could be represented by a matrix or higher-order array. R file containing a Shiny application, ending with an expression that produces a Shiny app object. For example, if I asked for 100,000 random numbers between 1 and 10 I would likely have an even distribution of all of them, but the mean would be 5. packages(‘animation’) • step 1 - write a function that generates the sequence of plots • step 2 - use one of the package functions to string plots. Snow relies on the Master/Slave model of communcation: One device (master) controls one or more other devices (slaves). dunif gives the density, punif gives the distribution function qunif gives the quantile function and runif generates random deviates. 1 Date 2015-04-30 Title Tests for Uniformity Author Maxim Melnik, Ruslan Pusev Maintainer Ruslan Pusev. On the other hand, runif returns a sample from a real-valued range. For example, when a subset of the covariates in the true model are highly correlated, the LASSO is prone to including one of the highly correlated covariates and ignoring the rest. Hello, I'd like to perform a regression using MCMCregress (MCMCpack). get out of R q() ## usually say NO on saving workspace when it asks, ## unless you want to inherit same objects next time. R Sample is useful for selecting a sample from a finite set of. Getting started with the boot' package in R for bootstrap inference The package boot has elegant and powerful support for bootstrapping. To conduct Levene's test in R, we can use the leveneTest() function from the car library, which uses the following syntax: leveneTest(response variable ~ group variable, data = data) As an example, consider the following data frame that shows how much weight people lost on three different weight loss programs:. let see how to generate stable sample of random numbers with set. Repeat Function in R: The Repeat Function(loop) in R executes a same block of code iteratively until a stop condition is met. 19709386) is the ninth element. Example 1: Let the games begin. Example Suppose we want to sample from a density whose graph is shown below. The Uniform Distribution Description. 1 ,β2) T of the model. Here I'm only refering to numeric and character functions that are commonly used in creating or recoding variables. an array with dimension num, ip and ir containing a sample of draws from the uniform distribution on the Stiefel manifold. The first argument specifies how many numbers. I want each subplot to be a different color. But that expressivity comes at a price: speed. a generated random dataset of class "acomp" or "rcomp" drawn from a uniform distribution on the simplex of D parts. test is available in R for performing t-tests. 456,digits=2) [1] …. (To practice working with functions, try the functions sections of this this interactive course. In general, fabricatr is going to be compatible with any existing packages you use to generate synthetic data in one of two ways: either using those packages to create variables within a fabricate call, or using those packages to make complete data frames which are then imported into a fabricate. function (n, min = 0 , max = 1 ). Neural Networks with R - A Simple Example Posted on May 26, 2012 by GekkoQuant In this tutorial a neural network (or Multilayer perceptron depending on naming convention) will be build that is able to take a number and calculate the square root (or as close to as possible). If you are new to both R and Machine Learning Server, this tutorial introduces you to 25 (or so) commonly used R functions. I can set redraw = TRUE, but the markers still blink. a transaction). For the example, I fit a linear mixed effects model using lmer (just because I happen to be working with mixed models, and they throw back convergence errors more often than GLMs), then used the update function to challenge it with random draws from my dataframe. Monte Carlo method is a very powerful and easy way to perform numerical integration on a function that may be difficult to integrate otherwise. io Find an R package R language docs Run R in your browser R Notebooks randtoolbox Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests. It can be a row number or column number or position in a vector. It let’s you specify variance-covariance structures for the residuals and is well suited for repeated measure or longitudinal designs. Luckily, it's not too hard to calculate our own expected p-values under the null. $(N_1,N_2)$ defines a point in Cartesian coordinates. This post includes several examples and tips of how to use dplyr package for cleaning and transforming data. Installing fonts in R The XKCD fonts are not installed in the system. sample samples from a fixed set of inputs, and if a length-1 input is passed as the first argument, returns an integer output(s). purrr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. The boot function needs a function that calculates the mean based on the resample of the data. In this example, We are ceiling all the records present in [Standard Cost] and [Sales Amount] columns. Example code below: # dpois r - calculate poisson distribution probability in r dpois(20, lambda=12) [1] 0. The easiest way to include data in an email is to use dput() to generate the R code to. ##### # CHAPTER 1 # ##### # factorials and binomial coefficients factorial(n) choose(n,k) # sample command n - 10; k - 5 sample(n,k) sample(n,k,replace=TRUE) sample(n. rowFtests and colFtests are currently implemented using matrix algebra in R. If you want to learn more about how the dashboards were created each example includes a link to it's source code. In the output, the number of the first element listed on the line is given in the square brackets. That is, it does not use explicitly spatial objects (classes). In this post, I want to focus on the simplest of questions: How do I generate a random number? The answer depends on what kind of random number you want to generate. Built-in Functions. a transaction). npindex computes a semiparametric single index model for a dependent variable and p-variate explanatory data using the model Y = G(XB) + epsilon, given a set of evaluation points, training points (consisting of explanatory data and dependent data), and a npindexbw bandwidth specification. It can accept three parameters: Number of observations desired; Starting point for distribution; Ending point for distribution; The example below requests 5 observations selected from a uniform distribution ranging between 4 and 6. Travelling salesman problem in R. The round function rounds the first argument to the specified number of digits. Does animation help?Making Animations (in R)More Examples animation package in R Is an R package to create and export animations to a variety of formats (HTML/JS, GIF, Video, PDF) • install. Generating Random Variables and Values of Density Functions Recall that if DIST represent a particualr distirbution, then the general synthax in R. If you want to learn more about how the dashboards were created each example includes a link to it’s source code. # # Comment: # # An example of a one-off image drawn using the grid system. This example generates one uniform random number:. Dotplots, traditionally drawn with graphpaper and pen, used to be a popular way to display distributions of small, heavily tied, sets of values. Unfortunately, it can also have a steep learning curve. , example(log) RSiteSearch("topic") does a full-text search of all the R documentation and the mailing list archives for information on topic (you need an active internet connection). the generator: 39: 39: #Rnorm <- rziggurat # The fast normal number generator: 40: 40. Now let's look at the first 10 observations. 2 Example: Valid Color Names. To generate an IID sample from a given distribution in R, we can use the family of functions r{name of the distribution}. Rmd └── src └── runif. Hello, I'd like to perform a regression using MCMCregress (MCMCpack). 19709386) is the ninth element. In my last post I said I wasn’t going to write anymore about neural networks (i. One can simulate random numbers from uniform distributions in R using runif function. This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. Topics in statistical data analysis will provide working examples. An array is created using the array() function. > round(22. Although R can calculate accurately to up to 16 digits, you don’t always want to use that many digits. This package was written by the most popular R programmer Hadley Wickham who has written many useful R packages such as ggplot2, tidyr etc. If an element of x is not integer, the result of dpois is zero, with a warning. If you continue to use this site we will assume that you are happy with it. A set of r orthonormal vectors in R^p is called an r-frame in R^p. The package provides high-level interface for using a workstation cluster for parallel computations in R. However, if you require a custom implementation, you can use rxExec to manually construct and manage a distributed workload. On the other hand, if you want to teach you R, you will need some data to play with. Understanding Bayesian Inference with a simple example in R! Hi there! Last summer, the Royal Botanical Garden (Madrid, Spain) hosted the first edition of MadPhylo, a workshop about Bayesian Inference in phylogeny using RevBayes. R Examples ls lsf. R Sample is useful for selecting a sample from a finite set of. Uniform Distribution. First, try the examples in the sections following the table. To generate numbers from a normal distribution, use rnorm(). In the previous examples the ID variables we used for merging uniquely identified observations in each data frame. seed() function it will produce different samples at different time of execution. Particularly when only dealing with point data such an approach may be practical. 10) are easily demonstrated using R. Data analysis can be slow. Input data: here input is a data frame with 3 columns prividing the X and Y coordinate of the cell and its value. ROC curve example with logistic regression for binary classifcation in R. hat - mean(exp(-x)) print(theta. Write a function histogram. If the provided name is a valid R color, is_color() should return TRUE. Wouldn't be surprised. I just changed two lines of the given source code because of deprecated rhmr function. With the exception of the composite spec, it is possible to reproduce all examples in R. Running jobs in parallel using rxExec. R color cheatsheet Finding a good color scheme for presenting data can be challenging. str ( 'package:stats' ). Compiled code. flexdashboard Examples The examples below illustrate the use of flexdashboard with various packages and layouts. It can be a row number or column number or position in a vector. Then, R loops are not that bad if you don’t use too many iterations (let’s say not more than 100,000 iterations). How to use the software R to visualize, calculate probabilities and percentiles for a uniform distribution. ##### # Statistical Learning and Data Mining Codes #### # Author: Xiaotong Shen, Chen Gao, Chong Wu #### # We illustrate how to use regularization in R. This manual illustrates how to use the R package ‘mesub’. In the previous examples the ID variables we used for merging uniquely identified observations in each data frame. In this chapter you'll learn how to improve performance by rewriting key functions in C++. For example the base R function runif only contains a single line that consists of a call to C_runif. Rakhshan and H. The R programming language has become the de facto programming language for data science. This packages estimates the regression parameters β = (βT. Description（描述） These functions provide information about the uniform distribution on the interval from min to max. 11 (page 32). The first example uses a uniform (rectangular) distribution. auc, omission, sensitivity, specificity. For the example, I fit a linear mixed effects model using lmer (just because I happen to be working with mixed models, and they throw back convergence errors more often than GLMs), then used the update function to challenge it with random draws from my dataframe. When sharing results with colleagues, it might be useful to compact everything in a single file. The default algorithm in R is Mersenne-Twister but a long list of methods is available. This example will go over an approach to reading this data into R and turning it into a network object. It presents the percentage of captured positive responses as a function of selected percentage of a sample. Today, I will discuss the tapply function. All require you to specify the number. Introduction. plot for plotting marginal effect estimates using saved inter. table,stata,code-translation Your intuition is correct. Hi, I am trying to use dunif and runif however, I have two problems: if I do dunif(1:10, min=1, max=10) I get 10 values, which summed give me 1. Generate a random number between 5. R offers us a variety of solutions for random number generation; here's a quick overview of some of the options. TERR does not have built-in memory allocation size limits, except those imposed by the operating system (for example, the 2 gigabyte limit on 32-bit Windows). SQL Server Tutorials, T-SQL Examples, Power BI Examples, Power BI Tutorials, R Programming Examples, SSIS Examples, Excel VBA Macros Examples. The continuous uniform distribution is the probability distribution of random number selection from the continuous interval between a and b. seed function in R:. sample(x, size, replace = FALSE, prob = NULL) sample. H(T) = −βT 1 Z −β2X +e, when X is not observed in the sample data. For example on a Windows PC or a Macintosh you can use the menu options. Development of the sp package began in the early 2000s in an attempt to standardize how spatial data would be treated in R and to allow for better interoperability between different analysis packages that use spatial data. Continuous Uniform Distribution in R (4 Examples) | dunif, punif, qunif & runif Functions. The mean and variance are E(X) = Var(X) = λ. The length of the result is determined by n for runif , and is the maximum of the lengths of the numerical arguments for the other functions. Though the above is purposely not a good example, Mapbox is capable of stunning customized cartography, which is available to R users in their cartography projects, Shiny applications, etc. Chi-squared test in R can be used to test if two categorical variables are dependent, by means of a contingency table. See the relevant part of the guide for better examples. Here are examples of the most common ones. For example if you have the function parsefile. To run this example: Download the train. One can simulate random numbers from uniform distributions in R using runif function. seed() function in R with example. R sample Function. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. dunif gives the density, punif gives the distribution function, qunif gives the quantile function, and runif generates random deviates. You should use R's dpois function. A good example may be the case where you want to optimize the hyper-parameters of a blend of predictions from an ensemble of multiple child models. Host genetics and diet, but not immunoglobulin A expression, converge to shape compositional features of the gut microbiome in an advanced intercross population of mice. In an (unbiased) random walk, each time step we move left or right with probability 0. 2 (on page 96) shows values for a deterministic spatial process z = 2x + 3y. Repeat Function in R: The Repeat Function(loop) in R executes a same block of code iteratively until a stop condition is met. I am moving 100 "particles" in both x,y dimensions and would like to plot the. Sometimes we need to do things slightly differently, using one-to-many merging. limit function. value (optional in the case of the t-test functions) and dm, the difference of the group means (only in the case of the t-test functions). In this Tutorial we will learn Repeat and Replicate function in R. a transaction). The R programming language has become the de facto programming language for data science. The Uniform Distribution Description. Dirk Eddelbuettel [email protected] GitHub Gist: instantly share code, notes, and snippets. The focus of the second section is on graphing discrete data. ##### # Statistical Learning and Data Mining Codes #### # Author: Xiaotong Shen, Chen Gao, Chong Wu #### # We illustrate how to use regularization in R. This includes infix operators like + , control flow operators like for , if , and while , subsetting operators like [] and \$ , and even the curly brace {. frames and presents some interesting uses: from the trivial but handy to the most complicated problems I have solved with aggregate. Package ‘SummarizedExperiment’. Date()" output: rmarkdown::html_document: toc: true toc_float: true toc_depth: 4 number_sections: true theme: "flatly" highlight: "textmate" css: "sevenbridges. Author(s) Yukai Yang, [email protected] Examples. As one might hope, proper use the arguments of the runif function makes code run faster in all types of time listed. Print contents of x x ## same as print(x) ## 2. ROC stands for Reciever Operating Characteristics, and it is used to evaluate the prediction accuracy of a classifier model. Topics in statistical data analysis will provide working examples. table,stata,code-translation Your intuition is correct. function (n, min = 0 , max = 1 ). It can be a row number or column number or position in a vector. R Markdown Example. 1 Getting a random number. Today, I will discuss the tapply function. You can use this to calculate the probability of getting X events within a period where the rate is Zs. (5 replies) Hi, I am trying to run thisK-Means clustering example on Rhipe with this whitespace seperated dataset. table("data. We can sample n values from a Levy distribution with a given location parameter (defined by the argument m, default is 0) and scaling parameter (given by the argument s, default is 1) using the rlevy() function. However, if there are a large number of computations that need to be. f by applying a […]. However, the markers move behind the polygon every other frame. With this R hypothesis testing tutorial, learn about the decision errors, two-sample T-test with unequal variance, one-sample T-testing, formula syntax and subsetting samples in T-test and μ test in R. packages(‘animation’) • step 1 - write a function that generates the sequence of plots • step 2 - use one of the package functions to string plots. Overview of random number generation in R R [https://cran. This splitting of the data is normally done in classification and regression to assess how well a model performs on new data. In R, we also have a nice implementation in a package called docopt, developed by Edwin de Jonge. The content of the post is structured like this: Example 1: Uniform Probability Density Function (dunif Function). (6 replies) Hello, I already sent such an email before Christmas, but nobody answered, so here is my problem: I would like to sample a population but the result needs to be reproducible, using 'runif' or 'sample' is the good way to do it but I can't manage to make the results reproducible even with the 'set. This blog is where we post additional examples for our books about SAS and R (Amazon: SAS and R. Snow relies on the Master/Slave model of communcation: One device (master) controls one or more other devices (slaves). Understanding Bayesian Inference with a simple example in R! Hi there! Last summer, the Royal Botanical Garden (Madrid, Spain) hosted the first edition of MadPhylo, a workshop about Bayesian Inference in phylogeny using RevBayes. Please see the example data sets below:. Plotting and Graphics. Example use case: You may want to figure out if big budget films become box-office hits. For example on a Windows PC or a Macintosh you can use the menu options. 2 posts published by Claudia Vitolo during July 2013. If an element of x is not integer, the result of dpois is zero, with a warning. The ceiling function in R programming also allows you to ceil the numeric values in a database or table columns. The Stiefel manifold is a collection of p \times r full rank matrices X such that X'X = I_r. Introduction. R, and the final result:. To clear some of this confusion, I’ve put together a few minimal reproducible examples to show how to make stochastic processes reproducible for various parallel backends: “multicore” backend “socket” backend “callr” backend; The examples of this post relate to the parallelMap and future packages. dunif gives the density, punif gives the distribution function qunif gives the quantile function and runif generates random deviates. 1 Random number generators in R-- the `r'' functions. Depending on the needs, you can program either at R command prompt o. One thought on “ Ejemplo en R: Muestreo con distribución uniforme (función runif) ” SERGIO CARDOZO PARRA on 12 marzo, 2018 Gracias, estaba buscando un ejemplo sobre la función runif y este fue preciso. seed is an integer vector, containing the random number generator (RNG) state for random number generation in R. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.