Math 319 - Outside
Introduction, Probability and Bayes' Theorem
Both of these books are on reserve in the Library:
In JADM read Judgment under uncertainty: Heuristics and biases pp.38-55 by Tversky and Kahneman
These authors have done classic work on the difficulty of making subjective estimates of probabilities. We saw a little of their work in the example in class about being a librarian and a feminist. Being aware of the pitfalls in making probability estimates should help you make more accurate estimates.
This article has some tough slogging and you are welcome to read and discuss it in groups.
What is meant by each of the following terms?
You should also read at least two of the following articles. In reading these articles I want you to pay attention to the general ideas, rather than the details, and to gain an appreciation of some of the practical problems we have in using utility theory, and to gain an appreciation of the wide spread application of risk analysis. You should also ask yourself if the authors have any biases you should beware of.
i. In JADM A computer-based system for identifying suicide attemptors p. 432-446 by Gustafson, Tianen and Greist.
This article compares a Bayesian and a regression model for predicting who will attempt suicide by first identifying those variables which seem to have most influence (e.g. lives alone, age, etc.), and then using both models. Each of the two models is developed based on data from staff at a mental health center and based on data from psychiatry residents. The models are used to predict both successful and unsuccessful attemptors.
Please note the following about the regression model: In Math 118 you learned how to use one variable, x, to predict another variable, y by fitting data to a line
y = a + b x
For example, if x is number of cigarettes smoked a day, and y is age at death you might develop an equation such as
y = 75 - 20 x
If you have more than one variable to use in prediction then instead of fitting a line to your data you fit a plane. If the variables are x1, x2, etc. then the equation becomes
y = a1(x1) + a2(x2) etc.
For example, if x1 is number of cigarettes smoked a day and x2 is % overweight then we might find an equation for y = age at death
y = 76 - 20 x1 - 5 x2
In RARM How risks are identified and assessed pp15-24 by Graham and Rhomberg. This article discusses public health risks by people in the field.
I will also be asking you to read Choices, Values and Frames by Kahneman and Tversky — reading notes and reference to be provided.