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Statistics and R for beginners
82 students

Statistics and R for beginners

Learn how to program statistical tests and write small programs in R. We cover basic math and statistics.
Created byCraig S Wright
Last updated 7/2012
English

Course content

2 sections • 10 lectures • 2h 21m total length

  • Lecture 123:00

    On completion of the subject students should be able to:

    1. Explain the basic concepts underlying estimation theory, hypothesis testing and regression;
    2.Explain the underlying assumptions and the applicability of each of the approaches studied;
    3.Determine appropriate methods for practical inference problems and apply such methods to data.
    4.Use R to program statistical tests
  • Lecture 220:00

    On completion of the subject students should be able to:

    1. Explain the basic concepts underlying estimation theory, hypothesis testing and regression;
    2.Explain the underlying assumptions and the applicability of each of the approaches studied;
    3.Determine appropriate methods for practical inference problems and apply such methods to data.
    4.Use R to program statistical tests

    Why do we need to use the R statistical package?
    We can use R for complicated statistical analyses or multiple calculations on a large dataset. It has powerful plotting, graphing, and data visualisation functions that are of professional quality. There are many freely available packages and libraries so that the user doesn’t have to waste time recreating the same functions. It is a fully programmable language, and is capable of connecting to relational database systems. In short, it is a versatile tool for data analysis and data mining, and it is very suitable for data assurance and auditing purpose. This tutorial and complied manual will give you the ‘fishing-rod’, so you can learn R at your own pace without going ‘Arrg’ and pulling your hair out!

  • Lecture 314:00

    On completion of the subject students should be able to:

    1. Explain the basic concepts underlying estimation theory, hypothesis testing and regression;
    2.Explain the underlying assumptions and the applicability of each of the approaches studied;
    3.Determine appropriate methods for practical inference problems and apply such methods to data.
    4.Use R to program statistical tests

    Why do we need to use the R statistical package?
    We can use R for complicated statistical analyses or multiple calculations on a large dataset. It has powerful plotting, graphing, and data visualisation functions that are of professional quality. There are many freely available packages and libraries so that the user doesn’t have to waste time recreating the same functions. It is a fully programmable language, and is capable of connecting to relational database systems. In short, it is a versatile tool for data analysis and data mining, and it is very suitable for data assurance and auditing purpose. This tutorial and complied manual will give you the ‘fishing-rod’, so you can learn R at your own pace without going ‘Arrg’ and pulling your hair out!

  • Lecture 416:00



    Why do we need to use the R statistical package?

    We can use R for complicated statistical analyses or multiple calculations on a large dataset. It has powerful plotting, graphing, and data visualisation functions that are of professional quality. There are many freely available packages and libraries so that the user doesn’t have to waste time recreating the same functions. It is a fully programmable language, and is capable of connecting to relational database systems. In short, it is a versatile tool for data analysis and data mining, and it is very suitable for data assurance and auditing purpose.

    This tutorial and complied manual will give you the ‘fishing-rod’, so you can learn R at your own pace without going ‘Arrg’ and pulling your hair out!

  • Workshop 1.18:49
    An introduction to starting and using R We will go through the initial steps to loading and using R in this workshop.
  • ACTpop
    This is the text file "ACTpop.txt" for the first workshop for those not wanting to use their own.
  • Workshop 1.25:35
    The second part of the workshop in learning R Remember to interactively run the commands. Type them and try altering them yourself.
  • Workshop 1.39:20
    We continue to learn the basics in R
  • Workshop 1.410:04
    We continue to learn the basics in R
  • Tutorial 1 Why Do We Need To Use The R Statistical Package35:00

    Why do we need to use the R statistical package?

    We can use R for complicated statistical analyses or multiple calculations on a large dataset. It has powerful plotting, graphing, and data visualisation functions that are of professional quality. There are many freely available packages and libraries so that the user doesn’t have to waste time recreating the same functions. It is a fully programmable language, and is capable of connecting to relational database systems. In short, it is a versatile tool for data analysis and data mining, and it is very suitable for data assurance and auditing purpose.

    This tutorial and complied manual will give you the ‘fishing-rod’, so you can learn R at your own pace without going ‘Arrg’ and pulling your hair out!

Description

On completion of the subject students should be able to:

1. Explain the basic concepts underlying estimation theory, hypothesis testing and regression;
2.Explain the underlying assumptions and the applicability of each of the approaches studied;
3.Determine appropriate methods for practical inference problems and apply such methods to data.
4.Use R to program statistical tests

Why do we need to use the R statistical package?
We can use R for complicated statistical analyses or multiple calculations on a large dataset. It has powerful plotting, graphing, and data visualisation functions that are of professional quality. There are many freely available packages and libraries so that the user doesn’t have to waste time recreating the same functions. It is a fully programmable language, and is capable of connecting to relational database systems. In short, it is a versatile tool for data analysis and data mining, and it is very suitable for data assurance and auditing purpose. This tutorial and complied manual will give you the ‘fishing-rod’, so you can learn R at your own pace without going ‘Arrg’ and pulling your hair out!

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