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Articles 1 - 30 of 35
Full-Text Articles in Statistics and Probability
Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire
Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire
Browse all Datasets
This data release provides historical ground-to-roof snow load ratio (GR) datasets used for snow load research and model development. The release includes original referenced datasets, cleaned country specific datasets, and a master dataset that combines Canadian and United States datasets into a standardized format for research and engineering applications.
P-Value Visualizer, Manish Rami
P-Value Visualizer, Manish Rami
Software
An interactive tool demonstrating what a user set p-value indicates with regards to probability.
Effect Size & Distributional Overlap Visualizer, Manish Rami
Effect Size & Distributional Overlap Visualizer, Manish Rami
Software
An interactive tool comparing a control group and a treatment group, both with standard scores (M = 100, SD = 15). Cohen's d is expressed in standard deviation units. The three shaded regions show what each group's distribution looks like and how much they overlap. You can either use the preset buttons for effect sizes (SLP benchmarks) or the slider to change the values of Cohen's d to examine the distributions.
Correlation Visualizer, Manish Rami
Correlation Visualizer, Manish Rami
Software
An interactive tool to understand correlations. The tool uses an example relationship between phonological awareness (CTOPP-2) and reading fluency. Both measures use standard scores (M = 100, SD = 15). Viewers can adjust r to explore how the strength and direction of correlation affects the scatter pattern and shared variance. Use the slider for r to see corresponding changes in the plot and the values of r and effect size.
Interactive Distribution Visualizer, Manish Rami
Interactive Distribution Visualizer, Manish Rami
Software
An interactive tool visualizing types of distribution. Viewers can morph between a bell curve, box plot, and cumulative frequency curve.
Reliability Vs. Validity Visualizer, Manish Rami
Reliability Vs. Validity Visualizer, Manish Rami
Software
A visualization tool to demonstrate the concepts of reliability and validity.
Each target represents repeated measurements of the same person or construct. The crosshair (✛) marks the true score. Reliability = how tightly shots cluster together. Validity = whether shots center on the true score. Click any panel for a clinical SLP example. Also see notes below the plots.
Gets: Greenhouse Environment Time Series, Scott Grimshaw, Natalie J. Blades, Grant R. Mcqueen
Gets: Greenhouse Environment Time Series, Scott Grimshaw, Natalie J. Blades, Grant R. Mcqueen
ScholarsArchive Data
This dataset contains high-frequency environmental measurements from a single greenhouse used to study multivariate statistical process control under strong autocorrelation. The data consist of a continuous Phase 1 monitoring period of approximately four weeks, during which environmental sensors recorded conditions inside the greenhouse once per minute.
The primary variables included in the archived dataset are:
- date – Date-time stamp at one-minute resolution (local greenhouse time).
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co2_ppm – Carbon dioxide concentration in parts per million (ppm).
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humidity_pct – Relative humidity (%).
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soil_temp_F – Soil temperature in degrees Fahrenheit.
Cohens_D, Manish Rami
Cohens_D, Manish Rami
Software
This Python script calculates the effect size Cohen's d in a two group situation with known means and Standard Deviations.
Use this effect size if the sample size in your experiment is large and the two SDs are similar.
Glass Delta, Manish Rami
Glass Delta, Manish Rami
Software
A Python script to calculate the effect size Glass' delta in a two group experiment with different standard deviation.
Supplementary Files For: "Structure Identification For High-Dimensional Data In The Vicinity Of Bear Lake", Ben Shaw, Haley Burger, Brennan Bean, Kevin Moon
Supplementary Files For: "Structure Identification For High-Dimensional Data In The Vicinity Of Bear Lake", Ben Shaw, Haley Burger, Brennan Bean, Kevin Moon
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This report focuses on seven water quality measurements taken at 43 different depths on the Bear Lake for the months of June - November in the years 2018 - 2023. These measurements create a high-dimensional dataset on which we apply state-of-the-art machine learning (ML) techniques to look for low-dimensional structure in the data. A similar effort was made for weather measurements taken near the lake. Our analysis revealed that water quality measurements tend to cluster (i.e., group together) by year, while weather measurements tend to cluster by time of the year. This suggests that the structure observed in the water …
Simulating Interventions To Improve Reproducibility In Scientific Publications, Ben G. Fitzpatrick
Simulating Interventions To Improve Reproducibility In Scientific Publications, Ben G. Fitzpatrick
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Supplementary Files For: Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma Watts, Brennan Bean
Supplementary Files For: Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma Watts, Brennan Bean
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Serious flooding can happen when rain falls on snow, which we call a rain-on-snow (ROS) event. Increasing our understanding of the behavior of floods resulting from ROS events can help us design better systems to manage flood water and prevent it from causing damage. This thesis explores how ROS events affect streamflow in the Western United States by examining the weather conditions that precede a streamflow surge. We classify stream surges as ROS or non-ROS induced based on these weather conditions, which helps us separate floods caused by ROS events from those caused by other factors. By comparing these different …
Artificial Intelligence Modeling Of Alzheimer's Disease And Environmental Science, Mohamed Abu Sheha
Artificial Intelligence Modeling Of Alzheimer's Disease And Environmental Science, Mohamed Abu Sheha
USF Tampa Graduate Theses and Dissertations
A data-driven statistical model operates as a mathematical illustration of a tangible issuefaced in reality, enabling the creation of predictions or decisions based on data. The process of utilizing probability and statistical principles in statistical models is essential for deriving meaningful conclusions from the data. The research conducted in this dissertation utilizes artificial intelligence (AI) models to integrate findings across health and environmental sci- ence.
The first research study in this dissertation, Alzheimer’s disease is a mental health issue and a brain aging dilemma that makes it difficult for older people to complete daily tasks without assistance. The physician uses …
Mathematical Modeling Of Tumor Response Dynamics To Predict Progression-Free Survival In Patients With Recurrent High-Grade Glioma, Daniel James Glazar
Mathematical Modeling Of Tumor Response Dynamics To Predict Progression-Free Survival In Patients With Recurrent High-Grade Glioma, Daniel James Glazar
USF Tampa Graduate Theses and Dissertations
In this dissertation, I aim to develop a mathematical model describing tumor volume response dynamics to perform individual dynamic predictions of progression-free survival (PFS) on patients with recurrent high-grade glioma (rHGG).
Patients with rHGG have a dismal prognosis with median overall survival (OS) of <12 months and median PFS of <7 months. However, there is a wide heterogeneity in treatment responses. Therefore, to aid clinicians with making decisions to alter therapeutic protocol, I would like to predict patient-specific PFS.
To perform individual dynamic predictions, I employ the Claret tumor growth inhibition (TGI) model. I further develop this model by coupling it with two different survival models. Inter-patient heterogeneity is also taken into account through mixed effects, including covariate effects. Model PFS predictions were evaluated using receiver operating characteristic (ROC) curve analysis as well as Brier …
12>Stochastic Analytical Predictive Models For Life Sciences And Crop Production Process, Erasmus Tetteh-Bator
Stochastic Analytical Predictive Models For Life Sciences And Crop Production Process, Erasmus Tetteh-Bator
USF Tampa Graduate Theses and Dissertations
Analytical predictive modeling uses algorithm-based mathematical, probabilistic and statistical methods to anticipate future events by identifying patterns in past data. It is a technique for predicting outcomes and a key application of statistical analysis in real-world scenarios. Real data-driven predictive models in various fields, such as life sciences, economics,or production industry, help individuals and institutions make data-driven informed decisions, which is essential for business success, providing companies with a competitive edge.
One of every five adult deaths is caused by heart disease and one person dies every 33 from cardiovascular disease in the United States according to the Center for …
Supplementary Files For "Using Digitized Building And Weather Records To Improve The Accuracy Of Ground To Roof Snow Load Ratio Estimations", Gideon Parry, Brennan Bean
Supplementary Files For "Using Digitized Building And Weather Records To Improve The Accuracy Of Ground To Roof Snow Load Ratio Estimations", Gideon Parry, Brennan Bean
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Reliability targeted snow loads (RTLs) measure the weight in accumulated snow (i.e. snow load) that a roof is required to support to ensure the probability of failure is suf- ficiently low. This calculation has historically relied upon a probability distribution that characterizes the ratio between the annual maximum ground snow load to the annual max- imum roof snow load, a quantity referred to as Gr. The best available data for estimating Gr comes from Canadian case studies from the 1950s and 1960s. However, much of the data was never digitized, with only approximations of data being made available in scanned …
Supplementary Files For: "Interactive Modeling Of Bear Lake Elevations In A Future Climate", Benjamin D. Shaw, Scout Jarman, Brennan Bean, Kevin R. Moon, Wei Zhang, Nathan Butler, Tommy Bolton, April Knight, Emeline Haroldsen, Abby Funk, Rebecca Higbee
Supplementary Files For: "Interactive Modeling Of Bear Lake Elevations In A Future Climate", Benjamin D. Shaw, Scout Jarman, Brennan Bean, Kevin R. Moon, Wei Zhang, Nathan Butler, Tommy Bolton, April Knight, Emeline Haroldsen, Abby Funk, Rebecca Higbee
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The water level, or elevation, of Bear Lake has a significant impact on agriculture, power, infrastructure, and recreation for communities around the lake. Climatological variables, such as precipitation, temperature, and snowfall, all have an impact on the elevation of Bear Lake. As the climate changes due to greenhouse gas emissions, the typical behaviors of these climate variables change, leading to new behaviors in Bear Lake elevation. Because of the importance of Bear Lake, it is vital to be able to model and understand how Bear Lake's elevation may change in the face of different climate scenarios and to gain further …
Calculations From On The Existence Of Periodic Traveling-Wave Solutions To Certain Systems Of Nonlinear, Dispersive Wave Equations, Jacob Daniels
Calculations From On The Existence Of Periodic Traveling-Wave Solutions To Certain Systems Of Nonlinear, Dispersive Wave Equations, Jacob Daniels
Mathematics and Statistics Student Research and Class Projects
In the field of nonlinear waves, particular interest is given to periodic traveling-wave solutions of nonlinear, dispersive wave equations. This thesis aims to determine the existence of periodic traveling-wave solutions for several systems of water wave equations. These systems are the Schr¨odinger KdV-KdV, Schr¨odinger BBM-BBM, Schr¨odinger KdV-BBM, and Schr¨odinger BBM-KdV systems, and the abcd-system. In particular, it is shown that periodic traveling-wave solutions exist and are explicitly given in terms of cnoidal, the Jacobi elliptic function. Certain solitary-wave solutions are also established as a limiting case of the periodic traveling-wave solutions, that is, as the elliptic modulus approaches one.
Msis-Glenn: Natural Selection In Wolves Leads To Domesticated Dogs Predicted By Agent-Based Model Simulations, Alex Capaldi, David C. Elzinga
Msis-Glenn: Natural Selection In Wolves Leads To Domesticated Dogs Predicted By Agent-Based Model Simulations, Alex Capaldi, David C. Elzinga
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Supplementary Files For "Adaptive Mapping Of Design Ground Snow Loads In The Conterminous United States", Jadon Wagstaff, Jesse Wheeler, Brennan Bean, Marc Maguire, Yan Sun
Supplementary Files For "Adaptive Mapping Of Design Ground Snow Loads In The Conterminous United States", Jadon Wagstaff, Jesse Wheeler, Brennan Bean, Marc Maguire, Yan Sun
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Recent amendments to design ground snow load requirements in ASCE 7-22 have reduced the size of case study regions by 91% from what they were in ASCE 7-16, primarily in western states. This reduction is made possible through the development of highly accurate regional generalized additive regression models (RGAMs), stitched together with a novel smoothing scheme implemented in the R software package remap, to produce the continental- scale maps of reliability-targeted design ground snow loads available in ASCE 7-22. This approach allows for better characterizations of the changing relationship between temperature, elevation, and ground snow loads across the Conterminous United …
A Course In Data Science: R And Prediction Modeling, Adam Kapelner
A Course In Data Science: R And Prediction Modeling, Adam Kapelner
Open Educational Resources
This is a self-contained course in data science and machine learning using R. It covers philosophy of modeling with data, prediction via linear models, machine learning including support vector machines and random forests, probability estimation and asymmetric costs using logistic regression and probit regression, underfitting vs. overfitting, model validation, handling missingness and much more. There is formal instruction of data manipulation using dplyr and data.table, visualization using ggplot2 and statistical computing.
Associations Among Plant-Based Dietary Indexes, The Dietary Inflammatory Index, And Inflammatory Potential In Female College Students In Saudi Arabia: A Cross-Sectional Study, Ghadeer S. Aljuraiban, Rachel Gibson, Leenah Al-Freeh, Sara Al-Musharaf, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert, Linda M. Oude, Queenie Chan
Associations Among Plant-Based Dietary Indexes, The Dietary Inflammatory Index, And Inflammatory Potential In Female College Students In Saudi Arabia: A Cross-Sectional Study, Ghadeer S. Aljuraiban, Rachel Gibson, Leenah Al-Freeh, Sara Al-Musharaf, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert, Linda M. Oude, Queenie Chan
Faculty Publications
Background Saudi Arabian diets are transitioning to more Western dietary patterns that have been associated with higher levels of inflammation. Emerging evidence suggests plant-based diets are related to lower levels of inflammation; however, the definition of plant-based diets varies. Objective The purpose of this study was to identify the extent to which an overall Plant-Based Diet Index (PDI), Healthy-PDI (hPDI), and Unhealthy-PDI (uPDI) vs Energy-Adjusted Dietary Inflammatory Index correlate with high-sensitivity C-reactive protein (hs-CRP) level. Design This was a cross-sectional study carried out at King Saud University. Data on dietary intake, anthropometrics, and hs-CRP were collected. Participants/setting Female students aged …
Supplementary Files For "Creating A Universal Depth-To-Load Conversion Technique For The Conterminous United States Using Random Forests", Jesse Wheeler, Brennan Bean, Marc Maguire
Supplementary Files For "Creating A Universal Depth-To-Load Conversion Technique For The Conterminous United States Using Random Forests", Jesse Wheeler, Brennan Bean, Marc Maguire
Browse all Datasets
As part of an ongoing effort to update the ground snow load maps in the United States, this paper presents an investigation into snow densities for the purpose of predicting ground snow loads for structural engineering design with ASCE 7. Despite their importance, direct measurements of snow load are sparse when compared to measurements of snow depth. As a result, it is often necessary to estimate snow load using snow depth and other readily accessible climate variables. Existing depth-to-load conversion methods, each of varying complexity, are well suited for snow load estimation for a particular region or station network, but …
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematics Ancillary Materials
This collection of student and instructor materials for Mathematical Modeling contains lesson plans, lecture slides, homework, learning goals, and student notes for the following major topics:
- Linear Functions
- Quadratic Functions
- Exponential Functions
- Logarithmic Functions
This is a materials update for a collection of materials created for a Round Nine ALG Textbook Transformation Grant.
How Data Is Changing The World Of Healthcare, Cameron Marous
How Data Is Changing The World Of Healthcare, Cameron Marous
Honors Capstone Enhancement Presentations
No abstract provided.
An Introduction To Copulas, Yifan Guo, Geng Zhang
An Introduction To Copulas, Yifan Guo, Geng Zhang
Capstone Showcase
Copulas are the mathematical functions that connect the distribution functions of univariate random variables to form multivariate distributions. We define copulas, present some of their key properties, and provide examples of their applications.
American Bittern (Botaurus Lentiginosus), Jennifer Smetzer, Toni Lyn Morelli
American Bittern (Botaurus Lentiginosus), Jennifer Smetzer, Toni Lyn Morelli
Second Century Stewardship Refugia Products
No abstract provided.
Where On Ice? Algorithmically Deconstructing Nhl Shot Locations As A Method For Player Classification, Devan Becker, Douglas G. Woolford, Charmaine B. Dean
Where On Ice? Algorithmically Deconstructing Nhl Shot Locations As A Method For Player Classification, Devan Becker, Douglas G. Woolford, Charmaine B. Dean
Western Research Forum
Where do hockey players shoot from? How does this vary from player to player? We present the results of a study that uses data-driven statistical methods to investigate these questions. The locations of shots by National Hockey League (NHL) players from 2011 to 2017 are analyzed using a combination of an image recognition algorithm and spatial statistical methodology. An unsupervised classifier is applied to output from a spatial point process model in order to determine which shot locations best characterize a given player. We define the number of regions a priori, but the image recognition algorithm chooses the shape …
Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey
Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey
Open Educational Resources
User-friendly Geographic Information Systems (GIS) is the common thread of this collection of presentations, and activities with full lesson plans. The first section of the site contains an overview of cartography, the art of creating maps, and then looks at historical mapping platforms like Hypercities and Donald Rumsey Historical Mapping Project. In the next section Google Earth Desktop Pro is introduced, with lessons and activities on the basics of GE such as pins, paths, and kml files, as well as a more complex activity on "georeferencing" an historic map over Google Earth imagery. The final section deals with ARCGIS Online …
Demonstration Databases (Supplemental To Psychology & Health Article), Blair T. Johnson
Demonstration Databases (Supplemental To Psychology & Health Article), Blair T. Johnson
CHIP Documents
Here is a database (in Stata, R, SAS, SPSS formats) that was used to demonstrate simple slopes analysis in meta-regression in an online supplement to the article, "Panning for the gold in health research: Incorporating studies’ methodological quality in meta-analysis," published in the journal Psychology & Health in 2014. It is an archive (zip) file that also contains the Stata syntax used in the demonstrations.