The quantities measured in a study are called random variables
, and a specific outcome is called an observation
. Several observations are collectively known as data
. The collection of all possible outcomes is called the population
. The variables may be qualitative or quantitative
. A third method which is sometimes used for qualitative data is called a pie chart
A set of data on its own is very hard to interpret. There is lots of information contained in the data, which is hard to see. We need means of understanding important features of the data, and to summarize it in significant ways. When the data are distinct and the occurrences refer to individual values, we demonstrate them graphically using a bar chart with heights of bars indicating frequencies. Statistics provides tools that are needed in order to respond logically to information you hear or read.
Mentioned below are some claims that we have heard on several occasions. All of these claims are statistical in character. The examples come from psychology, sports, health, business, law etc.
- 4 out of 5 dentists recommend Dentine.
- Almost 85% of lung cancers in men and 55% in women are tobacco-related.
- There is an 80% chance that in a room full of 50 people that at least two people will share the same birthday.
- People predict that it is very unlikely there will ever be another cricket player with a batting average over 425.
- A surprising new study shows that eating egg whites can increase one's life span.
- Women make 75 cents to every dollar a man makes when they work the same job.
- 77.48% of all statistics are made up on the spot.
Certainly, data and data interpretation emphasize practically every facet of modern life. Statistics are all around you, sometimes used well; and at most times not hence we must learn how to differentiate them. This will in turn make you into an intelligent consumer of statistical claims. The field of statistics is the science of learning from data. Statisticians offer important perception in defining which data and conclusions are reliable. Statisticians know how to solve scientific secrecies and how to avoid ploys that can trip up investigators.