Sayed Mostafa

Assistant Professor

North Carolina Agricultural and Technical State University

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Sayed Mostafa is an Assistant Professor at North Carolina Agricultural and Technical State University in the United States. His research primarily focuses on statistical methodologies, including bias correction techniques, survey data integration, and machine learning predictive performance. Recent publications highlight his work on bootstrap methods, nonparametric estimation, and text mining in big data analysis. Dr. Mostafa’s contributions enhance understanding of statistical practices in various research domains.

Articles (19)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Collaborators (6)

Tamer Elbayoumi

Assistant Professor

North Carolina A&T State University

UNITED STATES

View details

Emmanuel Obeng-Gyasi

Assistant Professor of Environmental Health and Safety

North Carolina Agricultural and Technical State University

UNITED STATES

View details

Ibrahim A Ahmad

Professor

Oklahoma State University

UNITED STATES

View details

Sarah Antar

University of Sheffield

UNITED KINGDOM

View details

Leonard Williams

North Carolina Agricultural and Technical State University

UNITED STATES

View details

Scott Harrison

North Carolina Agricultural and Technical State University

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Sayed Mostafa

Research Interests

Explore related searches

Contact this professor

About

Articles (19)

Bootstrap Methods for Correcting Bias in WLS Estimators of the First-Order Bifurcating Autoregressive Model

Composite Estimators for the Population Mean Under Ranked Set Sampling

Impact of Data Perturbation for Statistical Disclosure Control on the Predictive Performance of Machine Learning Techniques

Matched Mass Imputation for Survey Data Integration

Uncovering Patterns and Trends in Big Data-Driven Research Through Text Mining of NSF Award Synopses

Nonparametric model-assisted estimation from randomized response survey data

Bias Analysis and Correction in Weighted-<i>L</i><sub>1</sub> Estimators for the First-Order Bifurcating Autoregressive Model

An Analysis of the COVID-19-Induced Flexible Grading Policy at a Public University

Chronic Stress Indicator: A Novel Tool for Comprehensive Stress Analysis

Interaction Selection and Prediction Performance in High-Dimensional Data: A Comparative Study of Statistical and Tree-Based Methods

Association of Per- and Polyfluoroalkyl Substances with Allostatic Load Stratified by Herpes Simplex Virus 1 and 2 Exposure

The Association of Cytomegalovirus and Allostatic Load by Country of Birth and Length of Time in the United States

The Association of <i>Toxoplasma gondii</i> IgG and Liver Injury in US Adults

The Association of <i>Toxoplasma gondii</i> IgG Antibody and Chronic Kidney Disease Biomarkers

The impact of COVID-19 induced emergency remote instruction on students' academic performance at an HBCU

Lymphadenectomy and pelvic irradiation in high-risk endometrioid endometrial cancer: a population-based retrospective analysis using the SEER databank

The Association of <i>Toxoplasma gondii</i> IgG and Cardiovascular Biomarkers

On the estimation bias in first‐order bifurcating autoregressive models

Kernel Density Estimation Based on the Distinct Units in Sampling with Replacement

Collaborators (6)

Tamer Elbayoumi

Emmanuel Obeng-Gyasi

Ibrahim A Ahmad

Sarah Antar

Leonard Williams

Scott Harrison

Make your next move.