Introduction to Statistical Modelling and Inference Aitkin Murray
The complexity of large-scale data sets ("Big Data") has stimulated the development of advanced computational methods for analysing them. There are two different kinds of methods to aid this. The…
Specifikacia Introduction to Statistical Modelling and Inference Aitkin Murray
The complexity of large-scale data sets ("Big Data") has stimulated the development of advanced computational methods for analysing them. There are two different kinds of methods to aid this. The model-based method uses probability models and likelihood and Bayesian theory, while the model-free method does not require a probability model, likelihood or Bayesian theory. These two approaches are based on different philosophical principles of probability theory, espoused by the famous statisticians Ronald Fisher and Jerzy Neyman.Introduction to Statistical Modelling and Inference covers simple experimental and survey designs, and probability models up to and including generalised linear (regression) models and some extensions of these, including finite mixtures. A wide range of examples from different application fields are also discussed and