Master of Science in Applied Statistics Postgraduate Programme By University of Delaware Online |TopUniversities
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Master of Science in Applied Statistics

Location

Newark Campus, Newark, United States
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Main Subject Area

Statistics and Operational ResearchMain Subject Area

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Programme overview

Main Subject

Statistics and Operational Research

Degree

MSc

Study Level

Masters

Study Mode

Online

The M.S. in Applied Statistics provides a broad exposure to statistical theory while focusing on hands-on applications and model building using a case study approach.  The “applied” aspect of our program will be focused on using real data and making real decisions in analysis. 
Graduates of the Applied Statistics M.S. program will be able to:
  1. Demonstrate knowledge of statistical foundations in probability and mathematical statistics.
  2. Apply statistical tools such as regression, design of experiments, logistic regression and models of counts, and multivariate methods.
  3. Effectively use various software platforms including SAS, JMP, R and Python.
  4. Analyze a variety of data types and apply appropriate techniques as required by specific attributes of the problem and research goals.
  5. Conduct supervised statistical research that applies the tools and methods of statistics and data analysis.
  6. Demonstrate responsible and ethical professional conduct that respects diverse perspectives and promotes inclusivity.

Programme overview

Main Subject

Statistics and Operational Research

Degree

MSc

Study Level

Masters

Study Mode

Online

The M.S. in Applied Statistics provides a broad exposure to statistical theory while focusing on hands-on applications and model building using a case study approach.  The “applied” aspect of our program will be focused on using real data and making real decisions in analysis. 
Graduates of the Applied Statistics M.S. program will be able to:
  1. Demonstrate knowledge of statistical foundations in probability and mathematical statistics.
  2. Apply statistical tools such as regression, design of experiments, logistic regression and models of counts, and multivariate methods.
  3. Effectively use various software platforms including SAS, JMP, R and Python.
  4. Analyze a variety of data types and apply appropriate techniques as required by specific attributes of the problem and research goals.
  5. Conduct supervised statistical research that applies the tools and methods of statistics and data analysis.
  6. Demonstrate responsible and ethical professional conduct that respects diverse perspectives and promotes inclusivity.

Admission Requirements

3+
6.5+
79+

Sep

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