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STATISTICAL THEORIES
Once you have your data analyzed, you need to test your results. This is where statistical theories come in.
The field of statistics is quite different from the common idea we receive through newspapers and other media. In the media, the statistician is represented as a person who collects great amounts of quantitative data and then abstracts significant numbers from that information.
We all know that the determination of average hourly wages in an industry or the average number of children in urban American families is the statistician's job, but one who has taken even an introductory course in statistics knows that these examples are only a function of a much larger field.
Here we will introduce you to the concepts of inference, statistical tests, and hypotheses. These will be invaluable to you in your statistical analyses.
Inference
"To infer" means "to derive as a consequence, conclusion, or probability."
Example: Your colleague has just accepted a promotion to a position at the home office in another state. You infer that he will be relocating soon.
Inference is concerned with two types of problems:
- estimation of population parameters
- tests of hypotheses
A central topic in Human Resource administration is that of statistical inference.
In statistical inference, we are concerned with how to draw conclusions about a large number of events on the basis of observations of only a portion of them. Statistics provides the tools that formalize and standardize our procedures for drawing conclusions.