faculty
Uday Jha
Associate Teaching Professor
Decision & Information Sciences
Contact
508-999-8350
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Charlton College of Business 204
Education
2017 | Rochester Institute of Technology, Rochester, NY | MS Applied Statistics |
2012 | ICFAI University, Tripura, India | Master Aviation Management |
2009 | Madurai Kamaraj University, Madurai, Tamil Nadu, India | MS Physics |
2007 | ICFAI University, Tripura, India | MS Mathematics |
Teaching
- Applied Decision Techniques
- Supply Chain Management
- Introduction of Business Analytics
Teaching
Programs
Programs
- Business Administration MBA
- Business Administration Online MBA
- General Business Administration BS
- General Business Administration Online BS
- Healthcare Management MS
- Healthcare Management Online MS
- Juris Doctor & Master of Business Administration JD, MBA
- Operations Management—Business Analytics BS
- Operations Management—Business Analytics Online BS
Teaching
Courses
Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.
Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.
Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.
Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.
Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
A case study approach involving the following statistical concepts: descriptive statistics, probability, sampling, probability distribution, statistical estimation, chi-square testing, analysis of variance and simple regression-correlation analysis.
A case study approach involving the following statistical concepts: descriptive statistics, probability, sampling, probability distribution, statistical estimation, chi-square testing, analysis of variance and simple regression-correlation analysis.
Teaching
Online and Continuing Education Courses
A case study approach involving the following statistical concepts: descriptive statistics, probability, sampling, probability distribution, statistical estimation, chi-square testing, analysis of variance and simple regression-correlation analysis.
A case study approach involving the following statistical concepts: descriptive statistics, probability, sampling, probability distribution, statistical estimation, chi-square testing, analysis of variance and simple regression-correlation analysis.
Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.
Manufacturing and service applications of selected analytical decision-making tools and techniques. The course illustrates, by example, how manufacturing and service operations can apply quantitative tools to decisions involving queuing, staffing, scheduling, product mix planning, and inventory control.
Register for this course.
Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.
Register for this course.
A case study approach involving the following statistical concepts: descriptive statistics, probability, sampling, probability distribution, statistical estimation, chi-square testing, analysis of variance and simple regression-correlation analysis.
Register for this course.
Research
Research activities
- High Dimensional Multicollinear Datasets
Research
Research interests
- Big Data
- Business Analytics
Select publications
- Uday Kant Jha, Peter Bajorski, Ernest Fokoue, Justine Vanden Heuvel, Jan van Aardt, Grant Anderson, (2017).
Dimensionality Reduction of High-Dimensional Highly Correlated Multivariate Grapevine Dataset
Open Journal of Statis, 7, 702-717.
Rochester Institute of Technology ProQuest Dissertations Publishing - Uday Kant Jha, Peter Bajorski, (2017).
High-Dimensional Linear and Functional Analysis of Multivariate Grapevine Data
Uday Kant Jha holds an MS in Applied Statistics from Rochester Institute of Technology, Rochester, NY and an MS in Physics from Madurai Kamaraj University, India. He also holds an MS in Mathematics and a Master Aviation Management from the ICFAI University, India. He joined the University of Massachusetts Dartmouth for Charlton College of Business as a full-time lecturer in Fall 2016. He has been extremely active in advising undergraduate students. Uday Jha has had a very prominent presence at the college level with service. He is a faculty advisor for Data Fest, an annual event sponsored by American Statistical Association for students of Business and Computer Science. Uday Jha is an internship coordinator for the students of Decision & Information Sciences (POM). He has also served as the Graduate Program Director for the students of MS Technology Management during the Summer of 2023.
Latest from Uday
Mentioned in
- Apr 28, 2022 UMassD students win first place at DataFest 2022