Applied Statistics at Rochester Institute of Technology

Cost: Not available

Rochester Institute of Technology, USA

Type: Masters Duration: 2.5 years

Explore the Applied Statistics program at Rochester Institute of Technology. This program is offered in USA and provides an excellent learning opportunity in Masters studies.

The Master of Science in Applied Statistics at Rochester Institute of Technology (RIT) equips students with essential skills in statistical analysis applicable across various industries such as healthcare, marketing, and government. The program emphasizes data mining, machine learning, and the design of experiments, preparing graduates for high-demand roles in the job market. Students can choose to study either on-campus or online, with a flexible curriculum that allows for part-time study. The program culminates in a capstone project, integrating knowledge from coursework to solve complex real-world problems. RIT's strong focus on experiential learning, including co-op opportunities, enhances the educational experience, ensuring graduates are well-prepared for their careers. With a 100% outcomes rate and an average first-year salary of $109.1K, this program is designed for those looking to advance their careers in statistics and data science.

University
Rochester Institute of Technology
University Location
USA (Online)
Program Duration
2.5 years
Ranking
Not available
Part-time allowed
Yes

Required Courses
  • Foundations of Statistics
  • Applied Linear Models - Regression
  • Applied Linear Models - ANOVA
  • Capstone Thesis/Project
Elective Courses
  • Statistical Software- R
  • Statistical Quality Control
  • Design of Experiments
  • Survey Design and Analysis
  • Data Visualization & Storytelling
  • Lean Six Sigma Fundamentals
  • Predictive Analytics
  • Principles of Statistical Data Mining
  • Nonparametric Statistics and Bootstrapping
  • Multivariate Analysis
  • Times Series Analysis and Forecasting
  • Design and Analysis of Clinical Trials
  • Causal Inference
  • Categorical Data Analysis
  • Advanced Statistical Computing
  • SAS Database Programming