PhD Statistics – Statistical Informatics
Our mission at the Statistics – Statistical Informatics course at University of Arizona is to develop the next generation of data scientists, trained to meet the challenges of modern interdisciplinary data extraction, analysis, and interpretation.
|Full-time Duration:||2 years|
|Starting in:||August, January|
|Tuition Fee:||$10,063 per semester|
|Location:||Tucson, United States|
The Statistics – Statistical Informatics course at University of Arizona supports and encourages the central role of statistical and quantitative thinking in the biological, physical, engineering, financial, and social sciences.
Necessary training is provided for students to develop core expertise in statistical theory and methodology, and also for students who will apply their statistical knowledge in practical, transdisciplinary research; targeted subject-matter specialties include, but are not limited to biometry, bioinformatics, biostatistics, econometrics & financial statistics, educational statistics, operations research & applied probability, psychometrics, spatial/spatio-temporal analysis, statistical genetics/genomics, stochastic modeling, and quantitative risk assessment.
The Graduate College sponsors several Graduate Interdisciplinary Programs (GIDPs) in addition to the many interdisciplinary possibilities available through regular graduate degree programs.
GIDPs transcend departmental boundaries by facilitating cutting edge teaching and research at the nexus of traditional disciplines.
The high value placed on interdisciplinary research and education is indicative of The University of Arizona’s enthusiasm and commitment to fostering innovation and creativity among its faculty and students.
- Theory of Probability
- Theory of Statistics
- Advanced Statistical Regression Analysis
- Design of Experiments
- Statistical Consulting
“Choosing the Master’s program for Physiological Sciences at the University of Arizona was one of the best decisions I could have made in my education. Our department is warm and collaborative, offering an array of research topics and techniques underneath a vast and integrative umbrella of physiology. Beyond my research experience, I was presented with teaching opportunities, which I feel honed my skill of scientific communication. Having the dynamic research/teaching/class schedule not only kept me active but helped me reinforce material in multiple contexts. Overall, this program was exactly what I wanted in my segway into the medical sciences… and with my teaching assistantship paying for my tuition, how could I say no?”
Andrew Wojtanowski // MS 2016