## Olli Saarela (statistician)I am a Finnish statistician currently working as an assistant professor at the Department of Epidemiology, Biostatistics and Occupational Health of McGill University, Montreal, Quebec, Canada. I was born in Tuusula, Finland, and studied at the University of Helsinki. After obtaining my master's degree in 2004 (with a thesis on variance estimation from imputed survey data), I worked as a statistician in the cardiovascular epidemiology project MORGAM at the National Institute for Health and Welfare (THL), Helsinki, Finland. Meanwhile I also pursued PhD studies under the supervision of professor Elja Arjas and docent Sangita Kulathinal. I defendend my PhD thesis, entitled On probability-based inference under data missing by design, on 24 September 2010 against professor Ørnulf Borgan. My areas of interest include Bayesian inference, missing data problems, epidemiological study designs, in particular case-cohort and nested case-control designs, survival analysis, and fundamentals of statistical inference. |

- Mailing address: Department of Epidemiology, Biostatistics and Occupational Health, Purvis Hall, 1020 Pine Avenue West, Montreal, H3A 1A2 Quebec, Canada.
- Office: Room 49A of Purvis Hall.
- E-mail: first_name.last_name@mcgill.ca
- Work phone: 514-398-7518
- CV with publications

- Winter 2014: BIOS
602 - Epidemiology: Regression Models

- Fall 2013: EPIB 607 - Inferential Statistics

- R package for various risk model validation statistics, allowing
for weights (source/manual/example).

"Probability as degree of belief is surely known by anyone: it is that feeling which makes him more or less confident or dubious or sceptical about the truth of an assertion, the success of an enterprise, the occurrence of a specific event whatsoever, and that guides him, consciously or not, in all his actions and decisions."

Probability as so interpreted is a concept much more general than mere frequency. To quote Jaynes (2003, p. 292):

"In our terminology, a probability is something that we assign, in order to represent a state of knowledge, or that we calculate from previously assigned probabilities according to the rules of probability theory. A frequency is a factual property of the real world that we measure or estimate. The phrase 'estimating a probability' is just as much a logical incongruity as 'assigning a frequency' or 'drawing a square circle'.

The fundamental, inescapable distinction between probability and frequency lies in this relativity principle: probabilities change when we change our state of knowledge; frequencies do not. It follows that the probability p(E) that we assign to an event E can be equal to its frequency f(E) only for certain particular states of knowledge. Intuitively, one would expect this to be the case when the only information we have about E consists of its observed frequency; and the mathematical rules of probability theory confirm this in the following way."

(Goes on to Laplace's rule of succession.) To sum up, I am perfectly happy to study frequentist statistical methods, but at the same time acknowledging this difference between probabilities and frequencies.

Last updated: 2014-04-01