Data Science, Deep Learning, Machine Learning, Probability, Interview.
researchers aim to support with their data when conducting hypothesis tests. Type 1 Error and Type 2 Error Type I error A Type I error means rejecting the null hypothesis when it’s actually true. It means concluding that results are statistically significant when, in reality, they came about purely