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Essential Fundamentals of R

By: Geoffrey Hubona

  • 10:32:46
  • 53
  • 8
  • Language: English

Course Summary

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 sof

Read More

Target Audience

  • 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.

Pre-Requisites

Students will need to install both R software and RStudio 

Curriculum

  • Exercise Files
  • Introduction to R Software
    14:57
  • What is R?
    14:25
  • Workspace Management Controls
    15:37
  • Workspace Management R Manuals
    12:58
  • Hands-On Tutorial of R Basics (part 1)
    14:35
  • Hands-On Tutorial of R Basics (part 2)
    14:53
  • Tutorial with R Functions
    13:54
  • Distributional Functions and Plotting
    19:25
  • Exercise Files
  • Data Input and Output
    14:44
  • Accessing Data Sets in R
    14:40
  • Basic Data Structures (part 1)
    14:48
  • Basic Data Structures (part 2)
    14:42
  • Basic Data Structures (part 3)
    14:36
  • Manipulating Dataframes (part 1)
    16:04
  • Manipulating Dataframes (part 2)
    10:49
  • Input Output Exercises
    01:04
  • Dataframe Manipulation Exercises
    04:11
  • Exercise Files
  • Input Output Exercises Solution
    14:21
  • Data Manipulation Exercise Solution
    14:26
  • Manipulating Dataframes (part 3)
    07:48
  • Manipulating Dataframes (part 4)
    14:25
  • Manipulating Dataframes (part 5)
    18:37
  • Manipulating Dataframes (part 6)
    12:13
  • Exercise Files
  • Remaining Data Manipulation Exercises Solutions
    14:58
  • User-Defined Function Exercise and Finish Manipulating Dataframes
    15:44
  • Begin User-Defined Functions Demonstrations
    14:06
  • The 'Scope' of a Function
    14:16
  • Formal, Local and Free Parameters
    14:42
  • Flexible Arguments to Functions
    12:06
  • Exercise Files
  • User-Defined Functions Exercise Solution
    13:22
  • More on User-Defined Functions
    14:31
  • Loops and Repeats
    15:14
  • Control Statements
    16:05
  • Returning Values from a Function
    15:29
  • Anonymous Functions
    12:33
  • Exercise Files
  • Some Short Programs in R (part 1)
    15:13
  • Some Short Programs in R (part 2)
    16:02
  • The Apply family of Functions (part 1)
    16:11
  • The Apply Family of Functions (part 2)
    17:36
  • The Apply Family of Functions (part 3)
    11:47
  • Apply Functions Exercises
    08:23
  • Exercise Files
  • Apply Functions Exercises Solutions
    14:24
  • The Reshape Package in R
    12:05
  • Recoding Data in R (part 1)
    16:57
  • Recoding Data in R (part 2)
    15:50
  • More Vector-Maker Exercises
    06:59

About the Author

Geoffrey Hubona, Professor of Information Systems

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master's and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

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Essential Fundamentals of R

  • 10:32:46
  • 53
  • 8
  • Language: English
  • 15 days Money back Gurantee
  • Unlimited Access
  • Android, iPhone and iPad Access
  • Certificate of Completion

Course Summary

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 sof

Read More

Target Audience

  • 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.

Pre-Requisites

  • 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.

About the Author

Geoffrey Hubona, Professor of Information Systems

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master's and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

More From Author