Working scientists and engineers commonly feel that philosophy is a waste of time. But theoretical and philosophical principles can guide practice, so it makes sense for us to keep our philosophical foundations up to date. Much of the history of statistics can be interpreted as a series of expansions and inclusions: formalizations of procedures and ideas which had been previously considered outside the bounds of formal statistics. In this talk we discuss several such episodes, including the successful (in my view) incorporations of hierarchical modeling and statistical graphics into Bayesian data analysis, and the bad ideas (in my view) of null hypothesis significance testing and attempts to compute the posterior probability of a model being true. I'll discuss my own philosophy of statistics and also the holes in my current philosophical framework.
Other than being fun to play with and fun to illustrate, they serve a lot of important tasks for researchers. They can quickly identify which of 500 comparisons is statistically significant. They can offer data to show whether your brand users comprise 2 distinct groups of people or 7 distinct groups of people. They can offer data to show which price your consumers would refuse to pay. But there are two ways to use statistics.
The Society for Artificial Intelligence and Statistics is a nonprofit organization, incorporated in New Jersey (USA), dedicated to facilitating interactions between researchers in AI and Statistics. The Society has a governing board, but no general membership. The primary responsibilities of the Society are to maintain the AI-Stats home page on WWW, maintain the AI-Stats electronic mailing list, and to organize the biennial International Workshops on Artificial Intelligence and Statistics.
Since the passage of the Homeland Security Act of 2002, the Office of Immigration Statistics (OIS) has responsibility to carry out two statutory requirements: 1) to collect and disseminate to Congress and the public data and information useful in evaluating the social, economic, environmental, and demographic impact of immigration laws; and 2) to establish standards of reliability and validity for immigration statistics collected by the Department's operational Components.
Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. In applying statistics to, e.g., a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.