Economics 225: Elementary Business and Economic Statistics
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.
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.
- Simple linear regression.
- Analysis of variance.
- Multiple regression.