Discrete vs Continuous Distribution

Reply #13

LottoMetro — Thu, 20 Feb 2014 22:45:43 GMT

Nope.

Reply #12

greneggz — Thu, 20 Feb 2014 22:14:29 GMT

Hello first post BTW. Couldn't find the 'new member section'

While I agree with you that you would work with Integers (ie for the balls) and not using decimals or floats, what about normalization of the data.

So for example the your numbers range from 1-47 the number/ball 33 could be represented as 0.702

I would think, analyising the lottery for discrete vs continuos, we would encounter the problem that numbers are just numbers an there is not context of what '2' is or '33' is. Whe... [ More ]

Reply #11

SergeM — Tue, 18 Feb 2014 15:25:41 GMT

The distributions are mathematically the same. The amount of samples determins how the distribution looks like when you make a graph. So, the answer is, there is no most effective distribution as all distributions are in fact the same. The drawing has the last word. For lottery balls you work with integer counts, not with floats. You forgot the length of eternity in your calculation. (...) Does the past influence the future? You are on an eternal time line. The lottery may exist only for a small... [ More ]

Reply #10

SergeM — Tue, 18 Feb 2014 15:21:27 GMT

You wrote above that you use chi square test, but in fact you use a relative squared deviation frequency towards a mathematically averaged frequency for every number.

You made no point on why and how to take decisions. So there is no documentation on whether you increase or decrease your odds. There is no indication on how or what to pick and there is no mathematical proof to it.

Reply #9

SergeM — Tue, 18 Feb 2014 15:13:36 GMT

Lottobone: Will this work for Poker?

Maybe with 2 aces in your hand and 2 aces on the table

Reply #8

LottoBoner — Sun, 16 Feb 2014 00:58:26 GMT

This idea seems to be plausible for data storage, coin tossing, and stocks,

Will this work for Poker?

On a more serious note, Data is just Data.

There is no need for conversion. Conversion is an extra step. The point is to reduce steps.

I prefer Data Consolidation over Data Conversion.

You dont need to convert anything to locate a potential indicator.

Reply #7

SergeM — Sat, 15 Feb 2014 20:42:47 GMT

You mean statistical mathematics.

Reply #6

LottoMetro — Fri, 14 Feb 2014 22:31:39 GMT

Standard deviations,mean, median, sum, etc has nothing do with distributions, how so?

What I meant was that these things can be measured regardless of the distribution. If you have a set of data you can calculate all of these without even knowing whether the information follows a continuous or a discrete distribution. Distributions are useful mainly to find the central tendency of data.

Example, you have a set of numbers: 5, 19, 32, 56, 11, 40, 16. The mean of this sample would be 25.57,

Reply #5

adobea78 — Fri, 14 Feb 2014 22:12:37 GMT

Thanks very much for detailed explanation of the 2 distrubutions, am bit perplexed when you said, percentiles, quartiles, which i think are statistical measurements for parameters like , Standard deviations,mean, median, sum, etc has nothing do with distributions, how so? what tools(parameters) do you use to inteprete a said data? I understand countable variables are counted and continuous are measured.

Reply #4

LottoMetro — Fri, 14 Feb 2014 21:09:35 GMT

For the lottery? Not sure exactly what you are asking.

Lotteries are analyzed using discrete distributions: i.e. Poisson, binomial, and hypergeometric. We primarily use discrete in lottery because lottery consists of finite, countable variables. Percentiles, quartiles, and range has nothing to do with the distribution type....they can be measured in either one.

There are cases when a continuous distribution is close to discrete; for instance a uniform continuous distribution will resemble

Reply #3

adobea78 — Fri, 14 Feb 2014 20:52:41 GMT

You missed the intent of this topic, Discrete vs Continuous approach to data analysis, thanks for your input anyway.

Reply #2

SergeM — Fri, 14 Feb 2014 18:03:51 GMT

Explain me how you want to get better results in predictions. Naming tools means nothing.

Just look at the results in the simulations, how many percent of the posters actually get a full payback

Reply #1

adobea78 — Fri, 14 Feb 2014 16:04:45 GMT

Think of ' compressed file'(Zip), the elements of the file remains intact, but pool size(hopper) is reduced.The concept of subset is focus oriented, hence discrete random variables becomes the tenet of all workouts. Most of statistical parameters is geared towards Continuous random variables,which depicts Ranges and Estimates. The variables and outcome of lottery event is distinct, discrete and mutually esclusive, eg, flipping a coin is either Head or Tail, there's no in between,where as taking... [ More ]

Discrete vs Continuous Distribution

adobea78 — Thu, 13 Feb 2014 00:19:50 GMT

In analysiing data, which of the Distributions is most effective, and why