R Programming for Beginners: Getting Started
R Programming
| Beginner
- 13 videos | 1h 31m 25s
- Includes Assessment
- Earns a Badge
The free and robust statistical package R has been decades in the making and is worth learning for serious statistical operations, such as conducting new medical data analysis. This course teaches you everything you need to know to get started with R, from installing R to running R from the command line. You'll grasp how to invoke basic functions and view the documentation on those. You'll create variables in R and explore various reserved words and the = and
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseInstall and set up the r kernel on jupyter notebook on macosInstall and set up the r kernel on jupyter notebook on windowsUse the ? operator to view docs for functionsInvoke the help() function and create and use variablesIllustrate the use of reserved words and the <- and = assignment operatorsPerform math operations on variables
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Perform arithmetic operations using operators such as + and -Create variables using different techniquesUse various built-in functions such as print() and abs()Execute numeric built-in functions such as seq()Recall the different basic or atomic data typesSummarize the key concepts covered in this course
IN THIS COURSE
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2m 13sIn this video, you’ll learn more about your instructor and the course. In this course, you’ll start by installing R and Anaconda Jupiter on both Mac OS and Microsoft Windows. You’ll also run R from the command line. Then you'll invoke basic functions and view documentation using the question mark and double question mark operators before moving on to creating variables, exploring various reserved keywords, and the use of the equal to and arrow operators. FREE ACCESS
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8m 5sIn this video, you’ll watch a demo. In this demo, you’ll start with an exploration of R on the Macintosh platform. You’ll learn to install R and run R code from within a Jupyter notebook. First, you’ll download and install Anaconda. Then, you’ll set up a virtual environment for R, which will allow us to run the R kernel from within Jupyter notebooks. FREE ACCESS
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7m 18sIn this video, you’ll watch a demo. In this demo, you’ll explore the world of R. You’ll learn how to get started with R on a Windows machine. You’ll be running R from Jupyter notebooks. There are many advantages to doing it this way, notably the interactivity and the familiarity for those who come to R after having worked with Python. First, you’ll install Anaconda. FREE ACCESS
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7m 17sIn this video, you’ll watch a demo. In this demo, you’ll see a blank Jupyter notebook onscreen. In the top right you’ll see the R kernel is selected. R is an interpreted language, which means that it's perfect for an interactive environment like a Jupyter notebook. You’ll be able to type bits of R code into the code cells and then hit Shift Enter to have R evaluate them. FREE ACCESS
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8m 28sIn this video, you’ll watch a demo. In this demo, you’ll pick up where you left off at the end of the last one. You’ll make use of the ?? operator. Onscreen you’ll invoke the ?? operation has been invoked and followed with the word regression. You’ll see the word regression is not enclosed within double quotes. The ?? operator is going to return documentation about many different functions, which all contain the word regression. FREE ACCESS
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7m 21sIn this video, you’ll watch a demo. In this demo, you’ll start with variables and constants in R. Variables in R are just like variables in any other language. They’re used to hold values, and the point of a variable is that the associated value can change or vary over time. You’ll see R also has many different types of constants specifically for numeric types. FREE ACCESS
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7m 49sIn this video, you’ll watch a demo. In this demo, you’ll define more variables. Onscreen, we have a variable that makes use of the underscore. In early versions of R, variable names did not allow the underscore character. That's why it's very common to use the dot or the period instead. In this context, the dot, when used in a variable name in R does not indicate a struct or a class, or an object. FREE ACCESS
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8m 43sIn this video, you’ll watch a demo. In this demo, you’ll turn your attention from variables and constants to operators. You’ll get started with some simple and familiar operators. Onscreen you’ll see the + operator has been invoked to add to numeric values. Next, you’ll try out the - operator: 32 - 8.4 gives you 24.4. R also supports the multiplication and the division operators. FREE ACCESS
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5m 35sIn this video, you’ll watch a demo. In this demo, you’ll discuss other kinds of operators. You’ll start with logical operators. The ! is R's way of negating a condition. So !TRUE evaluates to FALSE and !FALSE evaluates to TRUE. You can think of the exclamation point as the complement operator in R. FREE ACCESS
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5m 35sIn this video, you’ll watch a demo. In this demo, you’ll turn your attention to various built-in functions in R. You’ll start with the print function. Here you’ll see you’ve passed in a string defined within a pair of double quotes into print. When you hit Shift Enter, you’ll see the output is the string you just passed in. FREE ACCESS
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8m 53sIn this video, you’ll watch a demo. In this demo, you’ll pick up with lists and vectors. Onscreen you’ll see the c function has been invoked. This collects different values and it returns a vector. In R, everything is a vector. Even individual numbers or strings are actually one-element vectors under the hood. The function c that you see invoked onscreen is short for combine, and what's returned is explicitly a vector. FREE ACCESS
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11m 26sIn this video, you’ll watch a demo. In this demo, you’ll turn to Data Types in R. You’ll start by invoking a common built-in function called typeof. You’ll invoke typeof passing in the value TRUE, all uppercase. You can see from the return value this is 'logical'. This allows you to say the data type of the value TRUE is logical. The same holds true for its mirror image FALSE. typeof FALSE also returns 'logical'. FREE ACCESS
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2m 41sIn this video, you’ll summarize what you’ve learned in the course. You’ve learned to install R as well as Anaconda on both Mac and Windows platforms to run R programs using Jupyter notebooks in a convenient interactive fashion. You also learned to create a special virtual environment which runs R on Jupyter notebooks using the conda package manager. You also learned to invoke basic functions in R from Jupyter notebooks. FREE ACCESS
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