
Explore the main file types in R, including R script, R markdown, text, C++ files, HTML outputs, and Shiny apps, and the four-window workspace in RStudio.
Explore the basic syntax of R, execute a hello world example, and create data frames for vectorized, table-like data using commands in the R console.
Explore the data types in R, including vectors, lists, matrices, arrays, factors, and data frames, and how variables reserve memory in the R Studio environment to store and classify values.
Learn to create and manipulate strings in R from text data, using single or double quotes, and perform concatenation, case conversion, nchar counting, and substring extraction.
Learn to create and customize histograms, bar charts, line charts, and scatter plots in R from scratch, using numeric vectors and data frames, exploring distributions, trends, and variable relationships.
Explore regression analysis, including linear and logistic regression, to model relationships between dependent and independent variables, and use R's lm to predict outcomes, estimate coefficients and intercept, and assess residuals.
Your journey will start with the theoretical background of object and data types. You will then learn how to handle the most common types of objects in R. Much emphasis is put on loops in R since this is a crucial part of statistical programming. It is also shown how the apply family of functions can be used for looping. In the graphics section you will learn how to create and tailor your graphs. As an example we will create boxplots, histograms and piecharts. Since the graphs interface is quite the same for all types of graphs, this will give you a solid foundation. There are lots of R courses and lectures out there. However, R has a very steep learning curve and students often get overwhelmed. This course is different. This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video, you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.
All the important aspects of statistical programming ranging from handling different data types to loops and functions, even graphs are covered. Learning R will help you conduct your projects. In the long run, it is an invaluable skill that will enhance your career. The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concepts. Various examples and data sets are used to explain the application.