Master of Science in Applied Statistics at University of Delaware

USD 32,070

University of Delaware, USA

Type: Masters Duration: 2.5 years

Explore the Master of Science in Applied Statistics program at University of Delaware. This program is offered in USA and provides an excellent learning opportunity in Masters studies.

The Online Master of Science in Applied Statistics at the University of Delaware is designed for working professionals seeking to enhance their analytical skills and meet the growing demand for data professionals. The program requires a minimum of 30 credit hours, divided into 15 credits of core courses and 15 credits of electives. Core courses cover essential topics such as regression analysis, multivariate methods, and experimental design, while electives allow for specialization in areas like time series analysis and biostatistics. The program is entirely online, providing flexibility for students to balance their studies with work and personal commitments. Students can complete the program part-time, typically within 18 to 30 months, and benefit from a curriculum developed by experienced faculty. Graduates are well-prepared for careers in various industries, leveraging their skills in data analysis and statistical methods to solve real-world problems.

University
University of Delaware
University Location
USA (Online)
Program Duration
2.5 years
Ranking
#506
Part-time allowed
Yes

Required Courses
  • STAT 611: Regression Analysis
  • STAT 613: Applied Multivariate Methods
  • STAT 615: Design and Analysis of Experiments I
  • STAT 670: Intro to Stat Analysis I – Probability
  • STAT 671: Intro to Stat Analysis II – Mathematical Statistics
Elective Courses
  • STAT 619: Time Series Analysis
  • STAT 621: Survival Analysis
  • STAT 656: Biostatistics
  • STAT 668: Research project
  • STAT 672: Python and Database Management
  • STAT 673: Econometrics and Statistics for Economics Research
  • STAT 674: Applied Data Base Management
  • STAT 675: Logistic Regression
  • STAT 666: Introduction to Python
  • STAT 666: Introduction to R