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What is Economics?
Quite often, in the news or in everyday conversation, we hear the word 'economics' used to describe forces that may influence the flow of goods across borders, monetary positions, or general financial health. However, economics is not merely a numerical discipline. It is a way of thinking about relationships and the trade-offs between competing wants and ends. This is primarily the job of an economist: to assess a situation, evaluate possible remedies, and make judgments on the future based on the past.

What's a regression?
One of the primary tools of the economist is a statistical tool called a regression. Frequently, economists are tasked with making predictions about the future of the economy or a particular industry. Since this is practically impossible to do with perfect accuracy, economists use data from the past to estimate what factors affect the force they are trying to measure and, given current conditions, what the effects of that force in the foreseeable future may be. Regression analysis provides the mathematical framework to test theories and hone predictions about trends yet to come.

Regressions can suck?
As with all generalizations or "educated" guesses, they have the potential to be misleading and may not accurately reflect the whole story. As author Gregg Easterbrook has said, “If you torture numbers long enough, they’ll confess to anything,” and many take advantage of this fact and the general public's misunderstanding of statistics to provide "evidence" supporting their own agenda. Many such "definitive" valuation methodologies can be deceptively inaccurate or even reckless. In short, some regressions just suck. YRS is meant to help convey some of the basics of statistical economics (econometrics) for the lay person as well as provide some insight into the "dismal science" upon which we unknowingly rely so much.

The Basic Principles
Below is a list of general terms to acquaint one with the tools of econometric valuation. While these are geared mostly for the student or novice economic enthusiast, they are described so as to be understood by the average person. Credit for the material and general approach go to Dr. Howard Hoffman and his interactive educational software, "Statistics Explained."

Terminology

Population The Statistic Z
Histogram Null Hypothesis
Mean Statistical Hypothesis
Median Alternative Hypothesis
Mode Type I Error
Range Type II Error
Standard Deviation Alpha
Variance Beta
Random Sample Power
Parameter Relationship Between Alpha, Beta, Power
Statistic Degrees of Freedom
Sample Mean The Statistic T
S Square T-Test
Sampling Distribution Statistic F
Unbiased Estimate F Test
Central Limit Theorem Sum of Squares
Standard Error Related Measures
Normal Distribution Correlation Coefficient
Transformation Rules Regression
Z-Score Regression Toward The Mean
Statistical Test Confounding Factor
Critical Region Chi Square
Two-Tailed Test ANOVA
One-Tailed Test Mean Square

 

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