ECON 27000 - Introduction To Statistical Theory In Economics And Business

Describing populations and samples; introduction to inference, including confidence intervals and hypothesis testing; correlation and simple and multiple regression; Chi-square, nonparametric, test of independence. Uses a popular statistical package for demonstrating and solving statistical problems.

Preparation for Course
P: MA 12401 or MA 11100 or MA 15300 or higher with grade of C- or better, or placement at or above MA 15300.
Sophomore or higher class standing.

Cr. 3.
Student Learning Outcomes
1. Explain core statistical concepts (such as probability, random variables, distributions, and the distinction between descriptive and inferential statistics) and describe their relevance for economic and business decision-making.
2. Apply methods of data collection, organization, and presentation using graphs, tables, and statistical software commonly employed in economics and business research.
3. Analyze and interpret quantitative and qualitative data using measures of central tendency, dispersion, frequency distributions, and graphical techniques.
4. Use probability theory and probability distributions (e.g., binomial, uniform, normal distributions) in modeling business and economic problems, and apply concepts such as expected value and conditional probability.
5. Construct and interpret confidence intervals; perform hypothesis testing to evaluate claims about economic or business phenomena using parametric and nonparametric methods.
6. Understand the properties and methods of statistical estimation, including least squares, method of moments, and maximum likelihood estimation.
7. Design, carry out, and assess simple regression and correlation analyses, including basic linear regression models as applied to economic and business data; interpret results to draw conclusions and guide decisions.
8. Recognize limitations in statistical inference, including issues of sampling error, selection bias, and the importance of experimental design in business and economics contexts.
9. Use statistical and data analysis software (e.g., Excel) to process and analyze real-world datasets, present results, and communicate findings effectively.
10. Apply quantitative reasoning and statistical analysis to solve problems and defend decisions in business and economic policy settings.