Are these results possibly the outcome of a probabilistic calculation?

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In summary, the text explores the possibility that certain results may stem from a probabilistic calculation, examining the implications of randomness and statistical methods in interpreting outcomes. It emphasizes the need to consider probability as a factor when analyzing results to understand their significance and reliability.
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An experiment about hazard and randomness applied to the fluctuation of the price of Bitcoin, without any use of math, A.I. and using very few data, gives very good results, Is it possible ? Give your annlyse.
Hello, I am seeking the opinion of specialists in statistics and probabilities to evaluate the results of a forecast on a univariate time series derived from an experiment at hazcard.com. They are presented as obtained from a logic that includes no probability calculation, no learning, no use of strategies, and only utilizes a limited history of 10 values as a working basis.

Can these results be considered possible, impossible, manipulated...

Thank you for your assistance.
 
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  • #2
I wouldn't believe them. Given the obvious ups and downs of the value of bitcoin, they would have a lot to prove.
 

FAQ: Are these results possibly the outcome of a probabilistic calculation?

Are these results statistically significant?

Statistical significance is determined by calculating a p-value, which measures the probability that the observed results could have occurred by chance. If the p-value is below a predetermined threshold (commonly 0.05), the results are considered statistically significant, suggesting they are unlikely to be due to random variation.

What is the role of randomness in these results?

Randomness can affect the outcomes of probabilistic calculations, as it introduces variability. Probabilistic models account for this by using probability distributions to describe the range of possible outcomes and their likelihoods. Understanding the role of randomness helps in interpreting the reliability and variability of the results.

How can we validate the results of a probabilistic calculation?

Validation can be done through repeated experiments or simulations, comparing the results with empirical data, and using statistical tests to assess the consistency and accuracy of the model. Cross-validation techniques and sensitivity analysis can also help determine the robustness of the results.

What assumptions are made in probabilistic calculations?

Probabilistic calculations often rely on assumptions about the underlying distributions, independence of events, and the parameters used in the models. It's crucial to understand these assumptions because they influence the results and their applicability to real-world scenarios. Violations of these assumptions can lead to inaccurate conclusions.

Can we predict future outcomes based on these probabilistic results?

Probabilistic results provide a range of possible future outcomes along with their likelihoods, rather than precise predictions. While they can inform decision-making and risk assessment, it's important to recognize the inherent uncertainty and potential for variability in future events. Probabilistic models are tools for understanding and managing uncertainty, not for guaranteeing specific outcomes.

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