ECON 2116 - Statistics II

The aim of Statistics II is to teach students the core concepts and application methods of inferential statistics. It is intended for students to make predictions about a population based on sample data, construct hypothesis tests, and statistically model relationships between variables. This course aims to increase the competency of providing data-driven evidence in economic decision-making processes.

The course starts with a review of sampling distributions and the central limit theorem. Point and interval estimation, confidence intervals, single and double sample hypothesis tests (Z and t-tests), and hypothesis tests for proportions are covered extensively. Subsequent sections deal with analysis of variance (ANOVA), Chi-square tests of independence and goodness-of-fit, and simple linear regression and correlation analysis.

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Newbold, P., Carlson, W. L., & Thorne, B. (2013). Statistics for Business and Economics. Pearson.Anderson, D. R., Sweeney, D. J., & Williams, T. A. (2017). Statistics for Business & Economics. Cengage.

Students are expected to comply with the principles of academic integrity in all examinations, coursework, and other academic activities. Information, data, tables, figures, and ideas obtained from external sources must be properly acknowledged. Plagiarism, manipulation of data or results, completing work on behalf of another student, and unauthorized collaboration are considered violations of academic integrity. Artificial intelligence tools may be used, when permitted by the course instructor, to clarify concepts, explore current labor market issues, or support the interpretation of data. Students are responsible for verifying the accuracy of information and interpretations generated by AI. AI tools may not replace students' own economic analysis, critical evaluation, or academic responsibility.