Basics of R Programming Language for Buddies

Explore data types in the basics of R, including numeric, integer, logical, and character. R is case sensitive, and the class() function identifies datatypes.

Vectors are one dimensional arrays in R that hold numeric, character, or logical data. Create them with c, use names function, and perform addition, sum, indexing, ranges, mean, and comparisons.

Master creating and manipulating matrices in R with the matrix function, byrow and nrow options, and apply cbind, rbind, and row and column sums in a film collection example.

Learn how factors store categorical data in R, with levels, named levels, and alphabetical ordering; use summary to count levels, and apply ordered true to enable meaningful comparisons.

Learn how to create and manipulate dataframes in R by combining vectors into a table, selecting rows and columns, and using subset, head, tail, and str to inspect structure.

Learn to create a list in R by combining a vector, matrix, and dataframe, name the items, and subset with [[ ]] to access elements and the diameter column.

Create a data frame with id and name, then export it to myfirst.csv using write.csv with row.names=FALSE to produce a two-column csv.

Learn how to import data into an R dataframe using read.csv from a csv file, or by choosing a file with file.choose, and store it as csvdata or csvdata1.

Explore flow control statements in R programming, including if-condition and else-condition, switch case, for loop, and while loop, with examples using numeric vectors and conditional outputs.

Explore pre-built functions in R, including the pipe operator %in%, rep, paste with the separator option sep, toupper, tolower, nchar, and seq(2,10,3) for sequence generation.

Learn how to create and call a user-defined function in R using the function keyword, pass arguments, and apply it in a for-loop to print multiples.

Learn to create graphs in R with a single plot() statement, including barplots, histograms, pie charts, and boxplots, using numeric x and y vectors.

Learn how to create a basic graph in R using the plot(x, y) function, and name the graph, x-axis, and y-axis with main, xlab, and ylab.

Learn to construct and customize histograms in R using hist(x), label axes with xlab and ylab, set a main title, and color the histogram with predefined colors or color codes.

Explore how to construct barplots in R using the barplot(x) function, color bars with col, add main titles, and create horizontal, stacked, and grouped barplots from vectors and matrices.

Construct a box plot from two numeric vectors using boxplot(formula), color it with col='red', and assign a main title to reveal min, max, and median values in the data.

Construct a pie chart using the pie() function with numeric regions and labels, color slices with rainbow(5), and create a 3D pie chart with plotrix and pie3D(), using explode 0.2.

Learn how to compute mean, median, variance, and standard deviation in R with the admissions dataset. Explore the syntax mean(admissions$admitted), median(admissions$admitted), var(admissions$admitted), and sd(admissions$admitted) for the admitted column.

Explore range, sum, quantiles, co-relation, and co-variance in R using admissions data, and learn to compute range(x), sum(admissions$admitted), quantiles, and cor or cov.

Explore binomial and poisson distributions in R, learning to query help, compute probabilities with dbinom and dpois, and obtain cumulative values with pbinom, ppois, and sum.

Explore the normal distribution in R with mean 100 and sd 10, use pnorm and dnorm, and learn the summary function to quickly summarize data frames.

Explore linear regression in R by modeling admitted versus applicants, interpreting correlation, coefficients, and residuals, and visualizing the best-fit line with lm and abline.