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Leili Soltanisehat

faculty

Leili Soltanisehat, PhD

Assistant Professor

Decision & Information Sciences

Curriculum Vitae

Contact

508-999-8445

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Charlton College of Business 322

Education

2022Industrial and Systems Engineering - University of OklahomaPhD
2018Engineering Management and Systems EngineeringMSc
2014Industrial and Systems EngineeringBSc

Teaching

  • Business Analytics
  • Operations Management
  • Intelligent Decision Sciences
  • Business Statistics

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.

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.

Research

Research interests

  • Model-based business analytics
  • Decision support system design
  • Data-driven-based environmental Systems
  • Sustainable and resilient infrastructures

Select publications

See curriculum vitae for more publications

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