Business & Quantitative Methods (BUQU)

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BUQU 1130  3 credits  
Business Mathematics  
Students will learn methods, procedures and applications of business mathematics, including the mathematics of merchandising, simple interest, and compound interest. Applications include discounts and markups, cost-volume-profit, short-term and long-term loans, credit card debt, savings and payment plan annuities, mortgages, bonds and investment decisions. Note: Students may earn credit for only one of ACCT 1130 or BUQU 1130, as they are identical courses.
Level: UG
Attributes: ASTR, BUSI, PW_2, QUAN
BUQU 1230  3 credits  
Business Statistics  
Students will learn statistical concepts, methods and procedures used in business, including descriptive statistics--graphics and numerical presentations, probability theory, sampling estimation, hypothesis testing and linear regression. The use of statistical software applications will form part of the course. Students will be expected to know, or to acquire on their own, basic Excel skills. It is recommended that students take either CBSY 1105 or CBSY 1110 in preparation or along with this course.
Level: UG
Attributes: ASTR, BUSI, QUAN
BUQU 3230  3 credits  
Applied Decision Analysis  
Students will learn to identify those business situations that require formal decision-analysis, to select the appropriate computer model, to run the model using computer software, and to interpret and describe the results. Students will investigate several case-studies portraying both good and poor decision-making skills and will make a formal presentation of their findings in a group setting. Students will learn to determine the optimal strategy for an organization, and to present a persuasive case for the adoption of that strategy. Students will develop skills in applying decision trees, forecasting and linear programming to real-world problems.
Level: UG
Prerequisite(s): One of the following: ACCT 1230, BUQU 1230, CRIM 2103, MATH 1115, MATH 2315, MATH 2341, PSYC 2300, SOCI 2365, or equivalent first-year statistics course.
Attributes: BUSI, QUAN

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