Why choose this Training Course?
The statistical analysis of numerical information is proven to be a powerful tool, providing everyday insight into matters like corporate finance, production processes and quality control. However, the advent of the Internet of Things, the consequential growth in Big Data, and the ever-increasing requirements to model and predict, mean that many of the analytical opportunities and needs of a modern, high performing company cannot be met using conventional statistical methods alone.
More and more companies are wrestling with complex modelling and simulation problems, addressing matters like trying to optimise production systems, to maximise performance efficiency, to minimise operating costs, to combat risk, to detect fraud and to predict future behaviour and outcomes.
This intensive PetroKnowledge training course is intended for delegates who have already attended the Data Analysis Techniques training course (this is a necessary prerequisite for this course) and hence who already have a solid understanding of conventional data analysis methods. This advanced training course shows by example how to build on the method learned in the Data Analysis Techniques course and to create a variety of powerful modelling, simulation and predictive analytical methods.
The methods introduced include Bayesian models, Newtonian and genetic optimisation methods, Monte Carlo simulation, Markov models, advanced What If analysis, Time Series models, Linear Programming, and more. The training course uses advanced features of Microsoft Excel throughout, and it is important that all delegates are fully competent in both Excel and the statistical analysis of data.