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Mar 29, 2026
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QM 501 - Introduction to Business Analytics
This course covers the fundamentals of statistics. It starts with defining data in the context of decision-making situations. Diverse types of data are explored focusing on data classification schemes, data summary statistics, and basic data graphical visualization. The concept of probability is covered with a singular and laser focus on normal and binomial probability distributions. The theory of sampling and sampling distribution is presented solving practical decision-making problems. The last part of the course focuses on confidence interval and test of hypothesis and their applications to data driven decision-making.
Credit(s): 1
Prerequisite(s):
None.
Outcomes
- Define data in context of decision-making situations.
- Identify discrete and continuous types of probability distributions.
- Use normal and binomial distributions to solve data-driven decision-making types of problems.
- Describe sampling and sampling distributions.
- Describe the application of the confidence interval and test of hypothesis to data-driven decision making.
- Solve confidence interval and test of hypotheses problems using t and Z probability distributions.
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