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Economics 225: Elementary Business and Economic Statistics

Sample Syllabus

Learning Objectives

The course will help students to accomplish the following:

  • Organize, display, and summarize data in a meaningful way, using tables and charts;
  • Compute and interpret measures of central tendency (mean, median, and mode);
  • Compute and interpret measures of dispersion (variance and standard deviation);
  • Know how to use both discrete and continuous distributions, including the binomial and normal distributions;
  • Understand sampling methods and sampling distributions;
  • Understand estimation and be able to compute confidence intervals;
  • Be able to carry out hypothesis tests;
  • Be able to compute and understand correlation coefficients and to perform simple linear regression;
  • Become proficient at carrying out statistical methods using spreadsheet software;
  • Understand the benefits and limitations of statistical analysis;
  • Be able to use statistical tools to enhance critical thinking.

Common Content

This document is a general guideline for all instructors of Elementary Business and Economic Statistics (Econ225). Items 1-13 are the recommended content for all Econ 225 courses, while individual instructors may include items 14-15 in their courses. This list shows the Economics faculty's expectation of minimum course content and does not restrict the individual instructor in any other way.

  • Introduction to business statistics and data.
  • Organizing and displaying statistical information using tables and charts.
  • Measures of central tendency or central location (mean, median, mode).
  • Measures of spread or variability or dispersion (variance, standard deviation).
  • Probability concepts, including conditional probability and independence.
  • Discrete probability distributions (Binomial and Poisson distributions).
  • Continuous probability distributions (Normal distribution).
  • Sampling methods and sampling distributions.
  • Estimation and confidence intervals.
  • Hypothesis testing: one-population tests.
  • Hypothesis testing: two-population tests.
  • Correlation.
  • Simple linear regression.

Optional Topics:

  • Analysis of variance.
  • Multiple regression.