Statistics for Data Analysis in R

This two day course is designed for those who analyse data or who are creating machine learning models, but who wish to firm their understanding in core concepts as well as expanding into types of data distributions, inferential statistics (hypothesis tests), statistical significance, and a deeper understanding of how linear regression works. It is expected that you will have experience with a programming language used for data analysis such as Python or R – if this is not currently the case we suggest completing one of our Python or R for Data Handling courses.As well as providing a business context to using core concepts such as averages, spread, and interpreting analyst visualisations, you will take this knowledge further and learn how distributions, sampling, and hypothesis testing can be used to analyse data in an organisation and in automatically highlighting significant results or anomalies.If you are on a learning journey with Machine Learning and AI this course will give you a strong starting point in the statistical methods that underpin a large number of algorithms without overloading you with too many mathematical formulae or notations that are otherwise commonly used to communicate advanced mathematics. Your focus will be on business problems and applying tools such as Python or R that you will need as part of this journey.Throughout the course you will engage with practical labs, activities, and discussions with one of our technical specialists. All modules involve the use of Python or R to practice the techniques taught – setting you up to succeed in analysing, interpreting, and getting value from your data.Target AudienceAnyone wishing to expand their understanding of Maths and Statistics related to Data Science. This course will provide all the required pre-requisite statistical knowledge needed for our more in depth programmes.