Dr. Joseph Caruso
Faculty Fellow
Bisgrove Hall, Second Floor, Room 254J
Office Hours:
M: 10 a.m. - 12 p.m.
W: 10 - 12 p.m.
T: 9:30 - 10:30 a.m.
TH: 9:30 - 10:30 a.m.
Phone: 716.286.8143
Website:
Biography
I am currently in my 8th year of teaching at Niagara University. As a Faculty Fellow at Niagara University, my IBM experience allows me to give students a “hands on” approach to solving business problems. In 2015 I was hired into the College of Business and am currently in the Finance/Economics Department.
My career at IBM began in 1978. At that time Poughkeepsie was the mainframe capital of the work and I began my journey as a systems analyst in the production control area. During my career at IBM I took advantage of all opportunities that were offered to me. I worked as a systems analyst, materials manager, statistician, market researcher, quality analyst and forecaster. Along the way I compiled an impressive list of credentials:
- PhD in Engineering Systems at Union College, NY.
- President of the Mid Hudson Valley Chapter of the American Statistical Association.
- published several external articles in the areas of software reuse and reliability.
- US patent in the area of survey analysis.
I ultimately attained a rank of senior systems analyst at IBM which was one step below director level. I was generally known as the “quantitative” analyst and often assisted other staff people with quantitative analysis.
Focus of Teaching
My focus of teaching at NU is Business Analytics. I have developed unique syllabus for Business Analytics where lecture is supplemented by three team presentations. I act as a consultant to students on project teams for a richer learning experience.
- Students are challenged with a descriptive statistics project with simulated data sets that resemble actual business data. Students analyze the data and generate graphics, tables and confidence intervals in Excel and/or R Studio.
- Students present chi-square analysis of contingency tables created by me where tables of data are generated using interactions and white noise so that all teams are on a level playing field.
- Student teams present stepwise regression and a regression tree analysis at the end of the semester using R Studio to introduce them to machine learning.
Current Involvement
- Member QAAC Committee
- Advisor for Manhattan College Business Analytics (MCBAC) Competition
Educational Background
- Ph.D. in Administrative and Engineering Systems, Union College 1992
- MS in Agricultural Economics and Operations Research,
- Penn State University 1978
- BA in Economics, SUNY at Stony Brook, 1974