The course is an introduction to the principles of statistics and their application to problems in business and economics. Topics include the basics of probability theory, descriptive statistics, sampling methods, statistical estimation, hypothesis testing, and the basics of linear regression.
Course Credits: 3
Prerequisites: MATH 1324 (Applications of Discrete Mathematics)
Student Learning Outcomes
By the end of this course, you will be able to:
- Describe the basic principles of good data collection.
- Explain the principles and basic techniques for sampling as a data collection method and apply these techniques to collect a sample.
- Explain the principles and basic techniques for experiments as data collection method and apply these techniques to conduct an experiment.
- Apply basic techniques to display data distributions with graphs and interpret these graphs.
- Apply basic techniques to display and summarize data distributions with numbers, including the following tools for describing relationships: scatterplots and correlation and linear regression.
- Explain the role of probability models when drawing conclusions from data.
- Explain, calculate, and interpret confidence intervals and tests of significance for population means and differences in population means.
- Explain, calculate, and interpret confidence intervals and tests of significance for population proportions and differences in population proportions.