Introduction to Data Analysis for Absolute Beginners

Introduction to Data Analysis for Absolute Beginners

Summary

This course introduces core concepts and skills in data analysis to those who are absolute beginners in the area. It is accessible for those with no experience of programming, no mathematics since high school, and no experience or training in data analysis.

It combines basic theoretical and practical components, presented in a gentle, accessible way. The focus is on intuition, simple language, pictures and experience rather than formulas, mathematical jargon, and rote learning.

Description

Course outline

Students will learn to input, process, and analyse data with a range of analytical and visualisation tools.

The course begins by covering types of data, data acceptance, input, processing, and transformation. It delivers a foundation in basic statistics, taught in an intuitive, accessible way that simplifies the learning experience. The instructor uses practical examples to give students valuable and engaging hands-on experience, providing a context in which theory is immediately relevant.

Risk analysis and probability theory will be taught using an intuitive, language-based approach that students will find familiar. The intuitive concepts presented will then be translated gently to the numeric domain.

Topics further into the course include key data-analysis techniques such as regression, correlation, spatial statistics, and time series. Practical exercises accompany discussion of each topic, building on the gentle, visual framework established in previous components.

A final core component of the course introduces concepts in business intelligence and reporting, including data summarisation, “slice and dice” analysis, and reporting of key performance and risk indicators.

Optional components, which may be presented depending on class interest and time available, include:

  • how to easily create spectacular interactive animations
  • social network visualisation and analysis
  • geospatial mapping
  • advanced time series forecasting and visualisation

Participants will use Microsoft Excel and the world’s most commonly used data analytics tool, R, which is readily available for free download and installation.


Core topics

  • Working with numbers
  • Time series and forecasting
  • Data basics
    • Input a dataset
    • Data preparation
    • Summaries
  • Measuring risk
  • Reporting: Metrics and KPIs
  • Making the numbers come alive: Animation


Equipment

Windows PCs running Excel and R with practical examples from all core components will be provided to attendees.


Prerequisites

This is a course for absolute beginners. There are no prerequisites.


Meals and refreshments

Morning tea, lunch, and afternoon tea will be provided.


Course instructor

The course will be led by Presciient director Dr Eugene Dubossarsky, or another Presciient instructor.

Dr Dubossarsky is the head of the Sydney Users of R Forum. Eugene is also Principal Founder of Analyst First, an international analytics industry organisation. He is a founder of the Institute of Analytics Professionals of Australia (IAPA); Director, University of New South Wales School of Mathematics and Statistics Industry Advisory Board; and a recognised industry leader in business analytics. Eugene is an experienced analytics professional with 20 years’ experience programming in R and its parent language, S.


Testimonials

I found the Introduction to R course extremely helpful. I have had very limited experience with R (and programming / statistical computing in general) and I now feel confident that I can use the language to do what I need with my data. The course was well designed and the notes are very helpful. I recommend this course to anyone who is new to R and wants to learn quickly. —Helen McCormick, PhD student, Epigenetics Laboratory, Victor Chang Cardiac Research Institute

The Introduction to R course provided clear and logical assistance to getting up and running with R. More than that, the real value was in providing guidance on the myriad of online resources and introducing me to a network of passionate and helpful R users. Eugene is a knowledgeable and approachable teacher. I wouldn't hesitate in recommending the course. I feel that I am now fully on the road to applying R and using data to improve efficiency across my organisation.
—James Orton, Data and IT Manager, UNICEF Australia

Thank you Eugene for advancing my R skills. I especially appreciate the time spent explaining the fundamentals of data manipulation — i.e. the code one needs to know before running any basic or sophisticated analysis. The pace of the workshop was perfect.
—Dr Chelsea Wise, Lecturer, Marketing, UTS Business School


Discounts

Please ask about our discounts for group bookings.


Feedback

Use enquiries@presciient.com.au to email us any questions about the course, including requests for more detail, specific content you would like to see covered, or queries regarding prerequisites and suitability.

If you would like to attend but for any reason cannot, please also let us know.

Variation

Course material may vary from what is advertised due to the demands and learning pace of attendees. Additional material may be presented along with or in place of what is advertised.


Cancellation

The course may be cancelled by the organisers with full refund of fees up to a week in advance of the scheduled commencement date.


Presciient training, coaching, mentoring, and capability development for analytics

Please ask about tailored, in-house training courses, coaching analytics teams, executive mentoring and strategic advice, and other services to build your organisation's strategic and operational analytics capability.

Our courses include:

  • Introduction to R
  • Predictive Modelling, Data Science and Big Data
  • Forecasting and Trend Analysis
  • Data Visualization
  • Data Analytics for Fraud and Anomaly Detection in Forensics and Security
  • Data Analytics for Campaign Marketing, Targeting and Insights
  • Data Analytics for Insurance Claims analysis
  • Data Analytics for Retail Marketing and Pricing
  • Data Analytics for the Web
  • Working with Data: Analysis and Report Writing for Everybody

Duration

2 Days

Upcoming Classes

No classes have been scheduled, but you can always Request a Quote.