A simple introduction to R and R studio

R is a powerful programming language and software environment commonly used for statistical computing and graphics. It provides a wide variety of statistical and graphical techniques, making it a preferred choice for data analysis, visualization, and machine learning tasks.

RStudio is an integrated development environment (IDE) for R that provides a user-friendly interface for writing, running, and debugging R code. It offers features like syntax highlighting, code completion, built-in tools for plotting, debugging, and package management, making it easier for users to work with R.

Key features and advantages of R and RStudio include:

1. Open Source: Both R and RStudio are open-source software, freely available for anyone to download and use. You can dowloand R from here and Rstudio from here.
2. Extensive Packages: R has huge numbers of packages for various statistical analyses, machine learning algorithms, data manipulation, and visualization.
3. Graphics: R provides powerful tools for creating high-quality plots and graphs for data visualization.
4. Reproducible Research: R and RStudio support reproducible research by allowing users to document and share their code, making it easier for others to reproduce their results.
5. Community Support: There is a large and active community of R users who contribute packages, tutorials, and help forums, making it easier to find support and resources.

Coding with Rstudio

Coding with RStudio is straightforward due to the simplicity of the R language compared to others. For instance, you can easily generate a numeric vector, perform various mathematical computations, or even define your own functions.

# Create a vector of numbers from 1 to 100
x <- 1:100
# you can call it by tabing x
x
# you can get the first values using head() function 
head(x)
# also you can get the last values using tail() function 
tail(x)
# you can generate another vector and called it y
y <- sqrt(x)
# plot 
plot(x,y)
# You can simply add a title or adjust the x-axis and y-axis.
plot(x,y, main="Simple plot", xlab="X", ylab="Square root of X")
        

To write your own function in R, you can begin by using function(). This function can accept as many arguments as necessary. Inside the curly braces, you define your mathematical function. Finally, you use return() to provide the desired result.

MyFirstFunction <- function(x,y){
  result <- (2*x) + y 
  return(result)
}

try <- MyFirstFunction(x,y) 
> head(try)
[1]  3.000000  5.414214  7.732051 10.000000 12.236068 14.449490        

Consistent practice in R is essential, gradually increasing the complexity of your code each time to progress as an R programmer.

I trust this brief and straightforward introduction to R has been beneficial.