Lognormal distribution in probability and statistics is used to model the distribution of a positive random variable Y, if Y = ln(X) has a normal distribution with mean μ and standard deviation σ.
Beta distribution is a family of distributions which are used to model the probability of continuous random variables defined on [0, 1]. There are two parameters , α and β in Beta distribution. A continuous uniform distribution defined on [0, 1] is actually a special case of a beta distribution, when both α and β equal 1.
Data file of unviersity testing score: University-Fullname-full.csv
read.table() function in R is often used when a delimited ASCII file (e.g. text file or csv file) is to be imported to generate a data frame. The basic syntax is
df <- read.table(input, options)
Data frames are the most widely used data structures in R programming. Unlike each element in vector/matrix/array must have same data mode, a data frame can store data elements with different mode or type in one object. For example, a data frame of family information can have numeric (e.g. age, income), character (e.g. name), and logical (work/not work) data types. Data frames in R act somewhat similar as a spredsheet in Microsoft Excel, where each row represents each observation or subject and each column refers to each variable or attribute.
When it is needed to store many elements of same type or mode into one data object in R, you can use array. Actually, vector and matrix are special types of array with one and two dimensions respectively.
If we want to store data of same mode or type in a two-dimensional array in R data analysis, matrix may be the most appropriate data structure to use. A matrix is just coming from a vector expanded in two dimensions with rows and columns, this is why the input subject is often a vector when a matrix is generated.
Vector in R programming is one-dimensional array. Its element can be numeric, character, or logital data. To create a vector in R, you can use function c().
Like in many other programming languages, packages in R are just collections of built-in functions and datasets are combined with R installation in a well-defined format. Library is directories where packages, either come with basic R installation or being manually installed, are stored on computer. In this post, we provide several important and useful functions associated with R package management.
RStudio acts as an computer-app for using R in a more freindly manner than the default R command window. Before using RStudio, R has to be installed first. In this post , we shortly introduce how to install R and RStudio on Windows.