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Improving Performance and Enhancing Introductory Statistics Using Projects

American Journal of Computational Mathematics 2017年第1期7卷 21-28页

作者： Joy D’Andrea rebecca wooten University of Florida Sarasota USA New College of Florida Sarasota USA

Introductory Statistics is a course taught in various community colleges, state colleges, and universities. Implementation of projects in this course has been shown to enhance students’ learning;in addition to increasing the ability of educators to assess students’ learning outcomes in detail. These projects are often inquiry-based and require a balance between flexibility and efficiency. Maintaining balance has provided the students’ opportunities through exploration and learner autonomy. In exploration, a student seeks new methods and options through experimenting. In this paper, we will discuss the benefits of exploration required by projects given in an introductory statistics course. The details of five different projects discussed in this paper—illustrate the practical influence that they could have on higher statistics courses.

关键词： Introductory Statistics Projects Inquiry-Based Learning Centered Active Learning

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Odds Ratio &Relative Risk Ratio of Buoy Conditions for Storms in the Atlantic Basin

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Open Journal of Statistics 2018年第5期8卷 747-759页

作者： Joy Marie D’Andrea rebecca Dyanne wooten Wendy Amanda Pogoda University of South Florida Sarasota-Manatee Sarasota Campus Sarasota FL USA Florida Southern College Lakeland FL USA Hillsborough Community College South Shore Campus Ruskin FL USA

The purpose of this paper is to bring awareness to the general public that certain conditions that occur at a buoy in the Atlantic Basin, such as wind located at the buoy, pressure located at a buoy, water temperature located at a buoy, atmospheric pressure located at a buoy, may be useful in helping predict when a hurricane could possibly hit the state of Florida in the future. One of the goals of this paper is to bring new statistical methods to investigate and analyze data, which will create better predicable measures in determining when a hurricane will possibly hit the state of Florida. In this paper, the topics of binary logistic regression and multinomial regression modeling are discussed in reference to their outcomes of both the odds ratio and relative risk ratio respectively. The coefficients from these models will show which prospective buoy conditions are possibly more responsible for indication of a storm being present in the Atlantic Basin. In this paper, the data that was used and compiled into a larger data set came from two different sources. First, the hurricane data for the years 1992-2013 came from Unisys Weather site (Atlantic Basin Hurricanes data) and the buoy data has been available from the National Buoy Center. In this paper, the variables of interest are: storm present, buoy wind speed, buoy pressure, buoy atmospheric temperature, buoy water temperature and buoy wind direction. The buoy conditions are the buoy wind, the buoy wind direction, the buoy pressure, buoy atmospheric temperature and the buoy water temperature.

关键词： Hurricanes Parametric Analysis Statistics Probability Distributions Odds Ratio

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On Heredity Factors of Parkinson’s Disease: A Parametric and Bayesian Analysis

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Advances in Parkinson's Disease 2018年第3期7卷 31-42页

作者： Abolfazl Saghafi Chris P. Tsokos rebecca D. wooten Department of Mathematics Physics and Statistics University of the Sciences Philadelphia PA USA Department of Mathematics and Statistics University of South Florida Tampa FL USA Department of Mathematics Florida Southern College Lakeland FL USA

Hereditary is one of the key risk factors of the Parkinson’s disease (PD) and children of individuals with the Parkinson’s carry a two-fold risk for the disease. In this article, chance of developing the Parkinson’s disease is estimated for an individual in five types of families. That is, families with negative history of the PD (I), families with positive history where neither one of the parents (II), one of the parents (III-IV), or both parents (V) are diagnosed with the disease. After a sophisticated modeling, Maximum Likelihood and Bayesian Approach are used to estimate the chance of developing the Parkinson’s in the five mentioned family types. It is extremely important knowing such probabilities as the individual can take precautionary measures to defy the odds. While many physicians have provided medical opinions on chance of developing the PD, our study is one of the first to provide statistical modeling and analysis with real data to support the conclusions.

关键词： Parkinson’s Disease Heredity Bayesian Estimation Maximum Likelihood Statistical Modelling

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