Tasting Experiment - Can Friend Distinguish Pepsi from Coke?

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SUMMARY

The discussion centers on a tasting experiment where a participant identified Coke and Pepsi correctly in 7 out of 10 trials. The key questions raised include the formulation of the null hypothesis and the appropriate statistical distribution for analysis. The null hypothesis should be that the participant's success rate is equal to random guessing (C = 0.5). A binomial distribution is confirmed as the correct model for this experiment, and the p-value can be calculated by summing the probabilities of achieving 7 or more correct identifications.

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musicgold
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Hi,

One of my friends was bragging that he could distinguish between Coke and Pepsi drinks just by taste. So I challenged him to taste drinks from 10 glasses and identify them as a Pepsi or a Coke. In five of the ten randomly arranged glasses, I had poured Pepsi and Coke in the remaining. He could correctly identify the drinks in seven out of the 10 glasses (C = 7, where C means correctly identified).

Now I am trying to analyze the result; however, I am not clear on two issues.

1. What should be the null hypothesis in this experiment, C = 0 or C = 10?

2. Which distribution to use? My guess is that I should be using a binomial distribution for this experiment, as there are only two outcomes for each trial. If that is correct, how do I find the p value of the experiment?
I know that the binomial distribution is a special case of the normal distribution, but not sure whether should I use the critical value tables for the normal distribution or t-distributions.

Thanks,

MG
 
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The usual idea would be to show that you can't reject the null hypothesis that p = 0.5 (that your friend just guessed well). You then add up the chance that the friend guessed 10, 9, 8, and 7 correctly (using the binomial distribution) and see how likely that is. If it's below 5% (or 100% - c, where c is your confidence -- I used the standard 95%) then you can't reject the possibility that your friend guessed well but can't tell them apart.
 

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