At the top of the Time-Machine app is a link "Leaders" where you can see a list of your fellow time travelers and their Z score ranks. What is a Z score?
Imagine you're in a class, and everyone just got their scores back from a big test. You're curious about how you did compared to the rest of the class. Did you score around the average, or were you way above or way below?
The average score of the class tells you the middle ground - what's typical. But just knowing the average isn’t enough. You also want to know how spread out everyone's scores are. That's where something called "standard deviation" comes in, which is a fancy term for the average amount scores differ from the average score.
Now, let's talk about the z-score. The z-score is a number that tells you how many standard deviations (or average differences) your score is from the average score of the class.
Here's a quick example:
If your z-score is 0, your score is exactly the class average.
If your z-score is 1, your score is one standard deviation above the average.
If your z-score is -1, your score is one standard deviation below the average.
So, the z-score is like a measuring stick, showing how far away from the average a score is.
Think of it like this: in a race, the average time tells you the typical time taken by racers. The z-score then tells you how much faster or slower a specific racer is compared to that average, measured in chunks of the typical difference (standard deviation).
A z-score also measures probability. A z-score is considered outside of chance expectation if it is higher than 1.7 standard deviations. So basically any z-score below 1.7 "could" result from chance expectation, but a z-score above 1.7 is "probably" due to something else aside from chance. That's why we like to use z-scores to measure your remote viewing performance. If you achieve a z-score above 1.7 this indicates that there must have been something more than just being "lucky" to score that high, because that's not likely to happen by chance alone. So you must have some skills! As you can see in the leader board above, time-traveler "Gelos" current Z score is a very significant 2.29. Recently, Mantraman also had a z-score above 2.0 but recently fell back. NICE WORK!
Just because you aren't scoring above 1.7 now doesn't mean that you aren't exhibiting any 'psi' skills. It may take more trials to get you to significance, or, it is possible that your contribution to our over-all consensus may stay small, but when we combine your predictions to all of the other prediction scores, this could result in an overall statistically significant value. For example, if we combined insignificant Z scores for 5 users, say: 1.6, .76, 1.5, -.2, 1.4 that works out to a total "Stouffer" z-score of 2.53 which is VERY significant!
WHAT IS THE TOTAL COMBINED Z SCORE FOR ALL TIME-MACHINE TIME TRAVELERS?
As of today, Oct 28, 2023, I have collected a total of 2287 trials from various users like you using the Time-Machine app over a period of 4 months. Following is a table showing the total simple binary z-score for all 2287 trials as well as resulting z-scores when we filter-out low scoring trials.
Score filter: | none | .5 | 1 | 1.5 |
Z score: | 1.82 | 2.49 | 1.52 | .89 |
Qty: | 2287 | 1403 | 768 | 363 |
% correct: | 52% | 53% | 53% | 52% |
As some of you know, we are also measuring "displacement". Displacement is when you intend to remote view the target for trial 3, but instead, perceive elements of the target for trial 4, 5, 1, and your lunch. Since we use an A.I. to do the analysis, we can also use it to compare your remote viewing transcript to all of the other 18 photos in the prediction (2 photos per trial x 9 trials). I'm not sure if I am actually aware of anyone else who has research displacement, so these findings are very interesting, and also very surprising. The table below shows the displacement z-scores:
Score filter: | none | 1 | 1.25 | 1.5 |
Z score: | .64 | 2.17 | 2.46 | 3.2 |
Qty: | 2107 | 714 | 501 | 328 |
% correct: | 51% | 54% | 55% | 59% |
As you also know, you complete 10 trials for one prediction, and we calculate a consensus prediction based on your 10 trials. Just using your intended trials only, when we use consensus to make a prediction about the outcome of your "prediction", then that works out to 233 predictions which are 57% correct resulting in a significant z-score of 2.16. You might ask, then why use a consensus of 10 trials when the z-score and % winning stat for displacement using a score filter of 1.5 is higher (z=3.2, 59%). Well, if you think about it, the displacement calculations REQUIRE all 10 trials, so we would have to complete them anyhow. Right?
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