Type I and Type II errors refer to rejecting or failing to reject the null hypothesis incorrectly in hypothesis testing. Statistical significance refers to the probability of obtaining test results by chance alone while practical significance considers the real-world importance of research findings. Common elements in all hypothesis tests include a null hypothesis, an alternative hypothesis, a test statistic, a significance level, and a decision to reject or fail to reject the null hypothesis.