Statistical Foundation of Data Analytics

Catalog description

Credits 3. 3 Lecture Hours. Collection, tabulation and presentation of numerical data; sampling, estimation of averages and variation, probability and error, hypothesis testing, linear and logistic regression; practical applications to functional problems in accounting, finance, marketing and management.