Statistics and R for beginners

Learn how to program statistical tests and write small programs in R. We cover basic math and statistics.
Instructed by Dr Craig S Wright
  • Lectures 10
  • Video 3 Hours
  • Skill level all level
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android

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Course 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!

What am I going to get from this course?

  • Over 10 lectures and 2.5 hours of content!

Curriculum

Section 1: Week 1
23 slides

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
20 slides

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!

14 slides

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!

16 slides



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!

08:49
An introduction to starting and using R We will go through the initial steps to loading and using R in this workshop.
91 B
This is the text file "ACTpop.txt" for the first workshop for those not wanting to use their own.
05:35
The second part of the workshop in learning R Remember to interactively run the commands. Type them and try altering them yourself.
09:20
We continue to learn the basics in R
10:04
We continue to learn the basics in R
35 slides

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!

Section 2: Week 2
Section 3: Week 3
Section 4: Week 4
Section 5: Week 5
Section 6: Week 6
Section 7: Week 7
Section 8: Week 8
Section 9: Week 9
Section 10: Week 10
Section 11: Week 11
Section 12: Week 12
Section 13: Review
Section 14: Test yourself

Instructor Biography

Dr Craig S Wright , Always learning

Dr Craig Wright is a lecturer and researcher at Charles Sturt University and executive vice –president (strategy) of CSCSS (Centre for Strategic Cyberspace+ Security Science) with a focus on collaborating government bodies in securing cyber systems.  With over 20 years of IT related experience, he is a sought-after public speaker both locally and internationally, training Australian and international government departments in Cyber Warfare and Cyber Defence, while also presenting his latest research findings at academic conferences.

In addition to his security engagements Craig continues to author IT security related articles and books.  Dr Wright holds the following industry certifications, GSE CISSP, CISA, CISM, CCE, GCFA, GLEG, GREM and GSPA. He has numerous degrees in various fields including a Master’s degree in Statistics, and a Master’s Degree in Law specialising in International Commercial Law. Craig is working on his second doctorate, a PhD on the Quantification of Information Systems Risk.

He has a Masters degree in Statistics from Newcastle University.

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