In a 95% confidence interval, if the true population parameter lies outside of the interval, it is considered a _______ error.
- Alpha
- Standard
- Type I
- Type II
In a 95% confidence interval, if the true population parameter lies outside of the interval, it is considered a Type I error. This is when the null hypothesis is true, but is incorrectly rejected.
Loading...
Related Quiz
- What is the difference between correlation and causation?
- How does skewness affect the relationship between the mean, median, and mode of a distribution?
- How is the 'mean' calculated for a data set?
- What can cause the Chi-square test for goodness of fit to be biased?
- How does the confidence level of an interval influence the width of that interval?