Q!!mG7VJxZNCI
3 Dec 2018 - 12:42:42 PM
Odds of a State Funeral on D5?
How many coincidences before mathematically impossible?
68–95–99.7 rule
Q
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Q is telling us that sometimes, there are deliberate events scheduled to derail what would otherwise be a big news day damaging to the DeepState Agenda. Here, there is an implication that Bush Sr’s funeral was scheduled to throw off the December 5th (D5) appearance of John Huber (although, Q also implied that Huber’s publicized appearance was a trap - and it looks like “they” took the bait). This is an example of the deep state using “ammunition”.
▶Anonymous 12/03/18 (Mon) 12:52:06 21113e (15) No.4130253
>>4130238
speculation is GHWB died weeks ago and it is just another deep state stall tactic to postpone the announcement in order to stall/push back whatever was supposed to happen on Dec 5.
D5 is the snowball that starts the avalanche
▶Anonymous 12/03/18 (Mon) 12:45:15 9d78e3 (3) No.4130121
>68–95–99.7 rule
In statistics, the 68–95–99.7 rule, also known as the empirical rule, is a shorthand used to remember the percentage of values that lie within a band around the mean in a normal distribution with a width of two, four and six standard deviations, respectively; more accurately, 68.27%, 95.45% and 99.73% of the values lie within one, two and three standard deviations of the mean, respectively. In mathematical notation, these facts can be expressed as follows, where X is an observation from a normally distributed random variable, μ is the mean of the distribution, and σ is its standard deviation:
Pr ( μ − σ ≤ X ≤ μ + σ ) ≈ 0.6827 Pr ( μ − 2 σ ≤ X ≤ μ + 2 σ ) ≈ 0.9545 Pr ( μ − 3 σ ≤ X ≤ μ + 3 σ ) ≈ 0.9973 {\displaystyle {\begin{aligned}\Pr(\mu -\;\,\sigma \leq X\leq \mu +\;\,\sigma )&\approx 0.6827\\\Pr(\mu -2\sigma \leq X\leq \mu +2\sigma )&\approx 0.9545\\\Pr(\mu -3\sigma \leq X\leq \mu +3\sigma )&\approx 0.9973\end{aligned}}} {\displaystyle {\begin{aligned}\Pr(\mu -\;\,\sigma \leq X\leq \mu +\;\,\sigma )&\approx 0.6827\\\Pr(\mu -2\sigma \leq X\leq \mu +2\sigma )&\approx 0.9545\\\Pr(\mu -3\sigma \leq X\leq \mu +3\sigma )&\approx 0.9973\end{aligned}}}
In the empirical sciences the so-called three-sigma rule of thumb expresses a conventional heuristic that nearly all values are taken to lie within three standard deviations of the mean, and thus it is empirically useful to treat 99.7% probability as near certainty. The usefulness of this heuristic depends significantly on the question under consideration. In the social sciences, a result may be considered "significant" if its confidence level is of the order of a two-sigma effect (95%), while in particle physics, there is a convention of a five-sigma effect (99.99994% confidence) being required to qualify as a discovery.
The "three-sigma rule of thumb" is related to a result also known as the three-sigma rule, which states that even for non-normally distributed variables, at least 88.8% of cases should fall within properly calculated three-sigma intervals. It follows from Chebyshev's Inequality. For unimodal distributions the probability of being within the interval is at least 95%. There may be certain assumptions for a distribution that force this probability to be at least 98%.
3 Standard Deviations From The Mean
THEY CAN’T DELAY THE INEVITABLE FOREVER
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