Applied Statistics Advanced certificate
Applied Statistics
Advanced certificate
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585‑475‑5288, rjpeqa@rit.edu
Overview
Engineers, analysts, and other professionals can develop a deeper understanding of the statistical methods related to their fields.
The advanced certificate in applied statistics is designed for engineers, scientists, analysts, and other professionals who want a solid education in the statistical methods that are most closely related to their work. Courses are available both on-campus and online to accommodate diverse schedules.
The program requires 12 credit hours and includes two core courses and two elective courses.
Curriculum
Applied Statistics, advanced certificate, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| STAT-641 |
Applied Linear Models - Regression
A course that studies how a response variable is related to a set of predictor variables. Regression techniques provide a foundation for the analysis of observational data and provide insight into the analysis of data from designed experiments. Topics include happenstance data versus designed experiments, simple linear regression, the matrix approach to simple and multiple linear regression, analysis of residuals, transformations, weighted least squares, polynomial models, influence diagnostics, dummy variables, selection of best linear models, nonlinear estimation, and model building.
|
3 |
| STAT-642 |
Applied Linear Models - ANOVA
This course introduces students to analysis of models with categorical factors, with emphasis on interpretation. Topics include the role of statistics in scientific studies, fixed and random effects, mixed models, covariates, hierarchical models, and repeated measures.
|
3 |
Electives |
6 | |
| Total Semester Credit Hours | 12 |
|
Admission Requirements
To be considered for admission to the advanced certificate in applied statistics, candidates should fulfill the following requirements:
- Complete a graduate application.
- Hold a baccalaureate degree (or equivalent) from an accredited university or college.
- Have satisfactory background in mathematics and statistics (two courses in probability and statistics).
- Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
- Have a minimum cumulative GPA of 3.0 (or equivalent) (recommended but not required).
- GRE scores are not required. However, in cases where there may be some question regarding the capability of the applicant to complete the program. Applicants may be asked to submit scores to strengthen their application.
- Submit a current resume or curriculum vitae.
- Submit two letters of recommendation from academic or professional sources.
- International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE. A minimum TOEFL score of 79 (internet-based) is required. A minimum IELTS score of 6.5 is required. The English language test score requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions.
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Additional Info
Grades
Students must attain an overall program grade-point average of 3.0 (B) for graduation.
Maximum time limit
University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.