How soon you can get 1 million views on slide-share !

I got a great formula, which is quite awesome and you can apply it if you want.

Lets say you want such and such number of views on your slide-share. Lets say 1 million. What you have to do?

step1- open your own website. Make sure it gets 100 views a day.
step2- open your slide-share, put N number of slide-shows. If N varies over time, views will vary accordingly.

How soon will you get a million views on slide-share?

Its 1million/(N*100*365) Years.

A new optimization parameter in a statistical sample !

It reflects the quality scope of the citations. Its the total percentage of a citation that goes into defining a particular citation index. Let me call it q-index therefore (q for quality)

See this example.

My h-ind is 60. So total (minimum) citation it accounts for is 60*60 = 3600. My total citation is 12215. So my q-ind is 3600/12215 = 29.47% Or 29.47% of my total citation were important for this parameter. Hence my q-index is 29.47. In this way if someone has 500 total citation with h-index 60, he has a much better q-index than mine, because more of his paper are highly cited

Whats the population; if male and female literacy is given as percentage.

May I add one more small note, see how easy it becomes to understand an “order of estimate”; A good student, that is one with a good maths background, should immediately pick up, population ~ 1.19 million. 61.26 % male. 58.04 % female. (Not only literate but total male and female). Then even, one question can be asked, what is male-female disparity, in terms of their population. (That is, without regard, to any further attributes, such as literacy numbers, or purchasing power distributions etc, which are btw non-existent variables in India, because research in India means Governmental Apathy.)

Its a slightly tricky question, if you already note, there is a mistake in the above, The % is not scaled to 100. Its an over-estimation by a factor of 1.193, and the really smart student recognizes this, (s)he doesn’t go and change all calculations. See how all numbers came just from the first few digits of the given numbers; 11,92,948 >> 1.19 million, vs over estimation factor; 1.193 (or less precise 1.19). Male: 6,12,597 >> overestimated percentage: 61.26. Female; 5,80,351 >> overestimated percentage: 58.04.

You would know they are over-estimated, because these two numbers, male and female population, while exclusive parameters, hence must add up to normal: 100 or 1.00, added up to 61.26+58.04 = 119.30, or (61.26+58.04)/100 = 119.30/100 = 1.193, do you see how easily, without doing any further adding etc, I caught the actual overestimation factor, above, to be 1.193? Cool Huh? Just from the first few numbers. If maths runs in your mind, you can do all these, if it doesn’t, but you have the right numbers, you will be led to believe nobody would catch your mistakes, and lie about the numbers. Possible. Just from the numbers as are stated, we can, catch the inconsistency, thats why maths education is important. In-fact, I committed the mistakes and wanted to catch the inconsistency, and from the calculations gradually caught it, so a more consistent picture was envisaged.

Mandela, Feynman, Statistics, Science and Religion.

Mandela and Feynman were born the same year. 1918. But while Feynman passed away in 1988, Mandela this year, it gives Mandela 25 more years to live (about 95 years old, Mandela). Thats a nearly 25% difference. What makes such wide disparity in how long people live?

On afterthoughts, (from this) statistics is a way of hiding our ignorance by allowing more and more attributes into a particular question, to the level our ignorance is no more useless. Thats the difference between science and religion: statistics. Statistics is the difference between science and religion. Religion brushes everything with one broom. Science needs various sizes for various tasks. In the end there is a difference even if its not so visible.