Hi guysIn my statistics book there is an example. They say that we

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SUMMARY

The discussion centers on the concept of statistical significance, specifically at the 1% level, in relation to observed occurrences versus theoretical expectations. The example presented involves 3 occurrences of type A against a theoretical expectation of 7, with a standard deviation of 1.65, resulting in a difference of 2.4 standard deviations. The participants clarify that a significance level of 1% indicates that any observed probability below this threshold is considered statistically significant, suggesting that such an event is unlikely to occur by chance. The conversation also addresses the interpretation of significance levels in the context of null hypothesis testing.

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  • Understanding of statistical significance and hypothesis testing
  • Familiarity with standard deviation and its calculation
  • Knowledge of Gaussian distribution and significance levels
  • Basic concepts of null hypothesis and alternative hypothesis
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  • Learn about the implications of different significance levels (e.g., 5%, 1%)
  • Explore the concept of Type I and Type II errors in statistical testing
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Niles
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Hi guys

In my statistics book there is an example. They say that we see 3 occurrences of type A, and theoretically expect 7. This is a difference of 4, since we know that the standard deviation is 1.65 (they calculate it), then the difference is 2.4 standard deviations. Looking at a table of the Gaussian, this is significant at the 1% level.

My question is regarding the significance at the 1% level. What is it they mean by that statement?
 
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If indeed the theoretical expectation is 7 with standard deviation 1.65, then of course it is possible that you get only 3 occurrences in any real experiment.
If you calculate the theoretical probability of actually observing this, you will see that it is very small. So if something with such a small probability does happen, this can hardly be a coincidence, and it is a significant event.
The significance level is just a mathematically sound way of saying what the term very small in the previous paragraph means. For example, taking a significance level of 1%, you consider any probability below 1% as very small (and therefore, if you actually observe such an event when you only run the experiment once or twice, it is significant).
 


That does make sense, thank you. I was viewing the significance level (SL) in the light of the null hypothesis. I always understood SL as being the probability that the event happened by chance from the null hypothesis. But in this example, the 3 occurrences of type (our null hypothesis) cannot "accidentally" yield 7 occurrences. So does this mean that my interpretation is wrong?
 

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