Basic probability theory, probability distributions of both discrete and continuous random variables, expectations, moments, distributions of functions of random variables, sampling distributions, estimations of population parameters, and hypothesis testing. Nonparametric statistical techniques and their applications to business research will also be covered in the course. Statistical computer software such as SAS or SPSS will be used in the course for data analysis.

Brief  review of matrices and their  operations - Vector Space: definition of vector space - linear independence and dependence – basis – dimension – orthogonality - dot and vector product - Matrices: rank - elementary row and column operations and their use in finding rank, inverse and solving linear equations systems - Matrix Partitions - Eigenvalues and Eigenvectors.  Prerequisite Math 140

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