When conducting an inferential statistical analysis, and applying a conventional “critical p- value” of .05, the odds of making a Type I Error and “rejecting a true Null Hypothesis” is…?
.05
To determine the odds of making a Type I Error and rejecting a true Null Hypothesis while conducting inferential statistical analysis with a conventional "critical p-value" of 0.05, you can calculate the significance level (alpha) associated with it. The significance level represents the probability of making a Type I Error.
In this case, the significance level (alpha) is set at 0.05, which indicates a 5% chance of making a Type I Error. This means that if the Null Hypothesis is indeed true, there is a 5% chance of wrongly rejecting it.
However, it's important to note that p-value and significance level are not the same thing. The p-value is the probability of observing the data or more extreme results, given that the Null Hypothesis is true, while the significance level is the threshold we set to determine whether the observed results are statistically significant or not.
By setting a significance level of 0.05, we are essentially saying that if the p-value is less than or equal to 0.05, we reject the Null Hypothesis. Therefore, there is a 5% chance of making a Type I Error by incorrectly rejecting a true Null Hypothesis.