Simple Philosophy of Statistics:
Jessica had fallen in love with Siva. I made this statement since I am the friend of Jessica. What is the basis upon which I made the statement “Jessica had fallen in love with Siva,” how I made the statement “Jessica had fallen in love with Siva,” how can I make a statement to reveal how close Jessica and Siva are, and how can one verify the statement “Jessica had fallen in love with Siva” is called as statistics by the learned people in the academic institutions. Statistics is the art of making, verifying and validating statements.
What is the basis upon which I made the statement?
The basis upon which I made the statement is observation – frequent observation of Jessica and Siva together. If I would have observed them once or twice, I would not have made the statement “Jessica had fallen in love with Siva.” I have observed them together frequently here and there. How frequently I have observed them together is called as frequency of observation. So, based on the frequency of observation I made the statement “Jessica had fallen in love with Siva.”
How close are they?
How close are Jessica and Siva? Are they very close? Are they just together? I can answer this question only by comparing with the standard love histories. Is it a normal love? Is it an abnormal love? [Comparing your observation with the help of standard curves like normal curve and other distribution curves]
How can one verify and validate that Jessica had fallen in love with Siva?
Am I a liar? Is my statement “Jessica had fallen in love with Siva” false? Is it an insignificant statement? If my statement is true and significant, one can expect Jessica and Siva to be together. If one observes Jessica and Siva together, my statement is true and significant. [Expected and observed Values]. If my statement is false or erratic, then what is expected will not be observed. The difference between the expected and observed values is called as „error value? by the great, great statisticians.
Everyone who could not understand this simple explanation would never understand the big, big, boopie statistic books or lectures by hotties on statistics!!
