Description

This is an introductory course which initially surveys the use and measurement of everyday economic statistics such as the GDP, the Index of Leading Economic Indicators, and the Consumer Price Index. The main focus of the course is an introduction to statistics with economic applications. Emphasis is on understanding and applying basic principles of statistical theory. The course will cover descriptive statistics, elements of probability theory, sampling theory, statistical estimation, regression analysis, and hypothesis testing. Assignments will use elementary econometrics and other statistical tools to examine economic data.

This course also provides the basic foundation needed (for economists and other social scientists) for the econometrics course (econ 327). The focus of the preparation is on applications to problems in economics. Applications include: techniques for organizing and summarizing economic statistical data; random variables and probability distributions; sampling distributions; estimation and hypothesis testing; and simple and multiple variable regression analysis. Computer Lab training and application sessions will be part of the course.

Diagram showing the difference between statistics and probability.
(Image by MIT OCW. Based on Gilbert, Norma. Statistics. Philadelphia, PA: W. B. Saunders Co., 1976. ISBN: 072164127X.)

Statistics

From Wikipedia, the free encyclopedia.

Statistics is a mathematical science pertaining to the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities; it is also used for making informed decisions in all areas of business and government.

Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics can be considered part of applied statistics. There is also a discipline of mathematical statistics, which is concerned with the theoretical basis of the subject.

The word statistics is also the plural of statistic (singular), which refers to the result of applying a statistical algorithm to a set of data, as in employment statistics, accident statistics, etc.