| Title | Two Centuries of Hypothesis Testing |
| Speaker | Eric Lehmann ASA Continuing Education Program Distinguished Statistician Video Series |
| Time | 3:00-4:00 p.m. |
| Place | PHY 013 |
| Title | Origins of Empirical Bayes (Butterflies, Oysters and Stars) |
| Speaker | Herbert Robbins ASA Continuing Education Program Distinguished Statistician Video Series |
| Time | 3:00-4:00 p.m. |
| Place | PHY 013 |
| Title | Statistical Environmental Models: Hurricanes. Predicting the birth of a storm, predicting the intensity of a storm and analysis of the Saffir-Simpson scale |
| Speaker | Rebecca Wooten |
| Time | 3:00-4:00 p.m. |
| Place | PHY 013 |
Abstract
The relationship between statistics and physics looking at the correlation between wind speed and pressure versus wind speed and temperature play a significant role in hurricane prediction. Contrary to previous studies, this study indicates that a drop in pressure is a result of the storm and less a cause. It shows that temperature is a key indicator that a storm will form in conjunction with a drop in pressure.
This study demonstrates a model that predicts the wind speed within a storm with a high degree of accuracy. With the verified model, we can perform surface response analysis to estimate the conditions under which the wind speed is maximized. Additional studies introduce a model that predicts the number of lightning strikes dependent on significantly contributing factors such as precipitable water, the temperatures within a column of air and the temperature range. Using extreme value distribution and historical data we can best fit flood stages, then including profiling estimate return periods.
| Title | A Multiple Regression Model for the Prediction of Average Annual Rainfall in Florida |
| Speaker | George W. Kimber, Jr. |
| Time | 3:00-4:00 p.m. |
| Place | PHY 013 |
Abstract
Several multiple regression models for the prediction of average annual rainfall in Florida will be presented and discussed. The nature, limitations, and potential of the original pilot study will be reviewed. A comparison will be made with a similar multiple regression model used to predict average annual rainfall in California. There will be an analysis of the underlying assumptions. The commands in SAS that generate the relevant procedures will also be demonstrated. A general discussion of the multiple regression procedures and of their interpretations will be presented.
| Title | Characterizations of Probability Distributions via Bivariate Regression of Record Values |
| Speaker | George P. Yanev |
| Time | 3:00-4:00 p.m. |
| Place | PHY 013 |
Abstract
We characterize the exponential distribution in terms of the regression of a function of a record value with its non-adjacent record values as covariates. We also consider a more general setting involving monotone transformations. We present special cases of characterizations involving weighted arithmetic, geometric, and harmonic means.
| Title | Parameter Estimation for the Distribution of Number of Children |
| Speaker | Julie Cholet |
| Time | 3:00-4:00 p.m. |
| Place | PHY 013 |
Abstract
The number of children born to a family may be modeled by the negative binomial distribution. However, the frequency class containing zero children is typically larger than expected under this distribution. There are two categories of childlessness. One consists of both deliberate choice and biological infertility, collectively labeled “sterility.” The other is the operation of chance. The latter category belongs to the negative binomial distribution, while the former does not. The inflation of the zero class due to presence of “sterile” families can make parameter estimation of the distribution difficult. We discuss three approaches to solving this problem.
Please direct questions to mthmaster@nosferatu.cas.usf.edu.
Last updated: 30-Nov-2006.
Copyright © 2000, USF Department of Mathematics.