Probability of next prediction being correct

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SUMMARY

The discussion centers on calculating the probability of a friend's prediction accuracy in social events, which is recorded at approximately 26.7%. The user has compiled two files: Binary.txt, detailing the true/false outcomes of predictions, and Incorrect.txt, which tracks the number of incorrect predictions before a correct one. The conversation highlights the misconception of using 'jitter' in predictions, referencing the gambler's fallacy, which suggests that past outcomes do not influence future probabilities.

PREREQUISITES
  • Understanding of basic probability concepts
  • Familiarity with statistical analysis tools
  • Knowledge of gambler's fallacy in probability theory
  • Experience with data representation in text files
NEXT STEPS
  • Research methods for calculating conditional probabilities
  • Explore statistical analysis using Python libraries like Pandas and NumPy
  • Learn about the gambler's fallacy and its implications in probability
  • Investigate techniques for improving prediction accuracy in uncertain environments
USEFUL FOR

This discussion is beneficial for statisticians, data analysts, and anyone interested in understanding prediction accuracy and probability theory in social event forecasting.

IMK
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Hello,
So a friend of mine has been predicting the outcome of social events and I have been recording the accuracy of his predictions as true if he accurately predicted the outcome or false if he was incorrect. The results of his predictions I have tabulated in the two attached files thus:

Binary.txt are the true/false status of his prediction in chronological order.

Incorrect.txt is a processed version of the Binary.txt where the values represent the number of incorrect predictions before he is correct again.

His mean accuracy is about 26.7% or about 1 in 3.74 predictions being correct.

So I was wondering if there is a way to calculate the probability of his next prediction being correct given what we know about he success rate and the amount of jitter is the sequence. Inasmuch as he sometime gets the next prediction correct or has gone as many as fourteen incorrect predictions.

Many thanks IMK
 

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I would not expect the 'jitter' to help you predict whether he will be right or wrong -- that seems to be a variant on the gambler's fallacy.
 
CRGreathouse said:
I would not expect the 'jitter' to help you predict whether he will be right or wrong -- that seems to be a variant on the gambler's fallacy.

Hello CRGreenhouse and many thanks for your reply.

So I am not sure what you are saying other than you have not disagreed with my simple 26.7% probability value. Is what I have done correct please? as I am not familiarly with the gambler's fallacy.

Again many thanks IMK
 

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