Statistical Tests
One-tailed and two-tailed statistical tests help determine how significant a finding is in a set of data.
When we think that a parameter might change in one specific direction from a baseline, we use a one-tailed test. For example, if we’re testing whether a new drug makes people perform better, we might only care if it improves performance, not if it makes it worse.
On the flip side, a two-tailed test comes into play when changes could go in either direction from the baseline. For instance, if we’re studying the effect of a new teaching method on test scores, we’d want to know if it makes scores better or worse, so we’d use a two-tailed test.
Tests of Significance: Process, Example and Type
Test of significance is a process for comparing observed data with a claim(also called a hypothesis), the truth of which is being assessed in further analysis. Let’s learn about test of significance, null hypothesis and Significance testing below.
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