Essential Fundamentals of R

Essential Fundamentals of R, available at $34.99, has an average rating of 3.95, with 46 lectures, based on 185 reviews, and has 1815 subscribers.

You will learn about Install R and RStudio and engage in a basic R session Understand the characteristics of different data types and structures in R Be able to read in data and write out data files from various sources Sort, select, filter, subset, and manipulate tables of data in R Create and execute their own user-defined functions in an R session Understand how to use the apply() family of functions to execute various actions against different R data structures Know how to use reshaping and recoding short cuts for changing data types and for rearranging data structures. This course is ideal for individuals who are Anyone who is interested in learning to use R software who is relatively new (or brand new) to using R or People who wish to learn the essential fundamentals of using R including data types and structures, inputting and outputting data and files, writing user-defined functions, and manipulating data sets or College undergrads and/or graduate students who are looking for an alternative to using SAS or SPSS software or Professionals engaged in quantitative analyses and/or data analyses tasks who seek an alternative to using SAS and/or SPSS software. It is particularly useful for Anyone who is interested in learning to use R software who is relatively new (or brand new) to using R or People who wish to learn the essential fundamentals of using R including data types and structures, inputting and outputting data and files, writing user-defined functions, and manipulating data sets or College undergrads and/or graduate students who are looking for an alternative to using SAS or SPSS software or Professionals engaged in quantitative analyses and/or data analyses tasks who seek an alternative to using SAS and/or SPSS software.

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Summary

Title: Essential Fundamentals of R

Price: $34.99

Average Rating: 3.95

Number of Lectures: 46

Number of Published Lectures: 46

Number of Curriculum Items: 46

Number of Published Curriculum Objects: 46

Original Price: $84.99

Quality Status: approved

Status: Live

What You Will Learn

Install R and RStudio and engage in a basic R session

Understand the characteristics of different data types and structures in R

Be able to read in data and write out data files from various sources

Sort, select, filter, subset, and manipulate tables of data in R

Create and execute their own user-defined functions in an R session

Understand how to use the apply() family of functions to execute various actions against different R data structures

Know how to use reshaping and recoding short cuts for changing data types and for rearranging data structures.

Who Should Attend

Anyone who is interested in learning to use R software who is relatively new (or brand new) to using R

People who wish to learn the essential fundamentals of using R including data types and structures, inputting and outputting data and files, writing user-defined functions, and manipulating data sets

College undergrads and/or graduate students who are looking for an alternative to using SAS or SPSS software

Professionals engaged in quantitative analyses and/or data analyses tasks who seek an alternative to using SAS and/or SPSS software.

Target Audiences

Anyone who is interested in learning to use R software who is relatively new (or brand new) to using R

People who wish to learn the essential fundamentals of using R including data types and structures, inputting and outputting data and files, writing user-defined functions, and manipulating data sets

College undergrads and/or graduate students who are looking for an alternative to using SAS or SPSS software

Professionals engaged in quantitative analyses and/or data analyses tasks who seek an alternative to using SAS and/or SPSS software.

Essential Fundamentals of R is an integrated program that draws from a variety of introductory topics and courses to provide participants with a solid base of knowledge with which to use R software for any intended purpose. No statistical knowledge, programming knowledge, or experience with R software is necessary. Essential Fundamentals of R (7 sessions) covers those important introductory topics basic to using R functions and data objects for any purpose: installing R and RStudio; interactive versus batch use of R; reading data and datasets into R; essentials of scripting; getting help in R; primitive data types; important data structures; using functions in R; writing user-defined functions; the apply family of functions in R; data set manipulation: and subsetting, and row and column selection. Most sessions present hands-on material that demonstrate the execution of R scripts (sets of commands) and utilize many extended examples of R functions, applications, and packages for a variety of common purposes. RStudio, a popular, open source Integrated Development Environment (IDE) for developing and using R applications, is also utilized in the program, supplemented with R-based direct scripts (e.g. command-line prompts) when necessary.

Course Curriculum

Chapter 1: Introduction and Orientation

Lecture 1: Introduction to R Software

Lecture 2: What is R?

Lecture 3: Workspace Management Controls

Lecture 4: Workspace Management R Manuals

Lecture 5: Hands-On Tutorial of R Basics (part 1)

Lecture 6: Hands-On Tutorial of R Basics (part 2)

Lecture 7: Tutorial with R Functions

Lecture 8: Distributional Functions and Plotting

Chapter 2: Input and Output, Data and Data Structures

Lecture 1: Data Input and Output

Lecture 2: Accessing Data Sets in R

Lecture 3: Basic Data Structures (part 1)

Lecture 4: Basic Data Structures (part 2)

Lecture 5: Basic Data Structures (part 3)

Lecture 6: Manipulating Dataframes (part 1)

Lecture 7: Manipulating Dataframes (part 2)

Lecture 8: Input Output Exercises

Lecture 9: Dataframe Manipulation Exercises

Chapter 3: Manipulating Dataframes in Depth

Lecture 1: Input Output Exercises Solution

Lecture 2: Data Manipulation Exercise Solution

Lecture 3: Manipulating Dataframes (part 3)

Lecture 4: Manipulating Dataframes (part 4)

Lecture 5: Manipulating Dataframes (part 5)

Lecture 6: Manipulating Dataframes (part 6)

Chapter 4: User-Defined Functions in R

Lecture 1: Remaining Data Manipulation Exercises Solutions

Lecture 2: User-Defined Function Exercise and Finish Manipulating Dataframes

Lecture 3: Begin User-Defined Functions Demonstrations

Lecture 4: The Scope of a Function

Lecture 5: Formal, Local and Free Parameters

Lecture 6: Flexible Arguments to Functions

Chapter 5: Writing Functions in R

Lecture 1: User-Defined Functions Exercise Solution

Lecture 2: More on User-Defined Functions

Lecture 3: Loops and Repeats

Lecture 4: Control Statements

Lecture 5: Returning Values from a Function

Lecture 6: Anonymous Functions

Chapter 6: The Apply Family of Functions

Lecture 1: Some Short Programs in R (part 1)

Lecture 2: Some Short Programs in R (part 2)

Lecture 3: The Apply family of Functions (part 1)

Lecture 4: The Apply Family of Functions (part 2)

Lecture 5: The Apply Family of Functions (part 3)

Lecture 6: Apply Functions Exercises

Chapter 7: Reshaping and Recoding Data

Lecture 1: Apply Functions Exercises Solutions

Lecture 2: The Reshape Package in R

Lecture 3: Recoding Data in R (part 1)

Lecture 4: Recoding Data in R (part 2)

Lecture 5: More Vector-Maker Exercises

Instructors

Geoffrey Hubona, Ph.D.
Associate Professor of MIS and Data Analytics

Rating Distribution

1 stars: 2 votes

2 stars: 7 votes

3 stars: 27 votes

4 stars: 78 votes

5 stars: 71 votes

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