BABS_V 500 (1.5) Applied Business Statistics I
This course is not eligible for Credit/D/Fail grading.
This course is not eligible for Credit/D/Fail grading.
Time series forecasting including common smoothing methods and autocorrelation methods; students will work with publicly available data. This course is not eligible for Credit/D/Fail grading.
Probability and models that incorporate uncertainty; working with data and extracting information to provide input for predictive and prescriptive analytic models within the Master of Business Analytics program. This course is not eligible for Credit/D/Fail grading.
Descriptive data analysis and extraction of useful information; predictive analytics and other clustering techniques; use of appropriate software. This course is not eligible for Credit/D/Fail grading.
Application of descriptive analytic skills to predictive analytics; using single/multiple regression, logistic regression and Poisson regression use of Discrete Choice Model. This course is not eligible for Credit/D/Fail grading.
This course is not eligible for Credit/D/Fail grading.
This course is not eligible for Credit/D/Fail grading.
This course is not eligible for Credit/D/Fail grading.
This course is not eligible for Credit/D/Fail grading.