a)The blank is the probability of erroneously rejecting the null hypothesis.I said level of significance, is that correct?
b)If you P value is 0.05. Does that mean that 95 times out of 100, the null hypothesis will be falsely rejected (I feel like it should be 5)
a, https://statistics.laerd.com/statistical-guides/hypothesis-testing-3.php You are correct, but most call it significance level. The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference.
b. if your p value is .05, The null hypothesis is rejected if the p-value is less than a predetermined level, α. α is called the significance level, and is the probability of rejecting falsely the null hypothesis given that it is true (a type I error). It is usually set at or below 5%. If your p is less than 0.05 and you REJECT the null hypothesis, then you have a risk of 5% of having falsely rejected it when it had to be accepted
a) Yes, you are correct. The blank in the question refers to the probability of erroneously rejecting the null hypothesis, and it is known as the "level of significance." The level of significance is typically denoted by the Greek letter alpha (α) and represents the maximum allowable probability of making a Type I error. In other words, it quantifies the likelihood of incorrectly rejecting the null hypothesis when it is actually true. Commonly used levels of significance include 0.05 (5%), 0.01 (1%), and 0.10 (10%).
b) No, that is not correct. The p-value is not equivalent to the probability of falsely rejecting the null hypothesis. Instead, it represents the probability of observing the obtained test statistic (or more extreme) results, assuming that the null hypothesis is true.
When the p-value is 0.05, it means that there is a 5% chance of observing the obtained test statistic (or more extreme) if the null hypothesis is true. Therefore, a p-value of 0.05 corresponds to a level of significance of 0.05. This means that if we set our level of significance at 0.05, we would reject the null hypothesis if the p-value is less than or equal to 0.05 (i.e., the results are considered statistically significant at the 0.05 level).
It is important to note that the p-value does not represent the probability of making a Type I or Type II error. Instead, it informs us about the strength of the evidence against the null hypothesis based on the observed data.