Significance Levels and Probability

In summary, the conversation discusses a study where 77 variables were measured on a sample of schizophrenic and non-schizophrenic individuals using 77 separate significance tests. Two of these tests were found to be significant at the 5% level, despite there being no actual difference between the two groups in any of the variables. The probability of one specific test showing a significant difference at the 5% level is 5%, and it is not surprising that 2 of the 77 tests were significant as 5% of 77 is almost 4. This probability can be interpreted as the long-term probability of making a type I error.
  • #1
ihearyourecho
61
0

Homework Statement



A group of psychologists once measured 77 variables on a sample of schizophrenic people and a sample of people who were not schizophrenic. They compared the two samples using 77 separate significance tests. Two of these tests were significant at the 5% level. Suppose that there is in fact no difference in any of the variables between people who are and people who are not schizophrenic, so that all 77 null hypotheses are true.

A) What is the probability that one specific test shows a difference significant at the 5% level?

B) Why is is not surprising that 2 of the 77 tests were significant at the 5% level?

Homework Equations



N/A

The Attempt at a Solution



I know this is a conceptual problem, but that's why I'm not getting it. I can do a problem if there are numbers, but I don't understand the concept of it I guess. If someone could just give me a general direction of where I'm supposed to go/what I'm supposed to do, I think I can get it.
 
Physics news on Phys.org
  • #2
I've come up with an answer for both A and B, but I'm not sure if they're right.

A) The probability is 5%.
B) It's not surprising because 5% of 77 is 3.85, so we expect almost 4 observations to be significant at the 5% level. These two observations could be two of those four.

If these are right or if these are wrong, I could still use a little explanation because I think I have a loose grasp on what's going on, but not a strong one.

Thanks :)
 
  • #3
Yes to both - one way (not the only way, but the appropriate way for this set of problems) to think of a significance level is that is the "long term" probability of making a type I error. the point of these two questions is to interpret it that way - and you did.
 
  • #4
Alrighty, thanks!
 

Related to Significance Levels and Probability

1. What is a significance level?

A significance level, also known as alpha (α), is the probability of rejecting the null hypothesis when it is actually true. It is typically set at 5% or 1% and represents the amount of evidence needed to reject the null hypothesis and support the alternative hypothesis.

2. How is a significance level determined?

The significance level is determined by the researcher prior to conducting the statistical test. It is usually chosen based on the level of risk the researcher is willing to take in making a decision. A higher significance level (e.g. 5%) means a greater chance of making a Type I error, while a lower significance level (e.g. 1%) means a lower chance of making a Type I error.

3. What is the relationship between significance level and p-value?

The significance level and p-value are closely related. The significance level is used to determine the threshold for rejecting the null hypothesis, while the p-value is the probability of obtaining results as extreme as or more extreme than the observed results, assuming the null hypothesis is true. If the p-value is less than or equal to the significance level, then the null hypothesis is rejected.

4. How do significance levels and probability relate to statistical power?

Statistical power is the probability of correctly rejecting the null hypothesis when it is false. As the significance level increases, the statistical power decreases. This means that a higher significance level makes it more likely to make a Type I error (incorrectly rejecting the null hypothesis), but also makes it less likely to make a Type II error (incorrectly failing to reject the null hypothesis).

5. Can significance levels and probability be used to prove causation?

No, significance levels and probability can only be used to determine the likelihood of obtaining certain results by chance. They do not prove causation, as there could be other variables or factors that are influencing the results. To establish causation, additional research and experiments need to be conducted.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
22
Views
2K
  • Precalculus Mathematics Homework Help
Replies
5
Views
4K
  • Precalculus Mathematics Homework Help
Replies
3
Views
1K
  • Precalculus Mathematics Homework Help
Replies
6
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
30
Views
2K
  • Materials and Chemical Engineering
Replies
12
Views
707
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
951
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
1K
  • Precalculus Mathematics Homework Help
Replies
4
Views
1K
  • Precalculus Mathematics Homework Help
Replies
7
Views
4K
Back
Top