I learned from the text that hypothesis testing is a “Procedure for deciding whether the outcome of a study (results from a sample) supports a particular theory or practical innovation (which is thought to apply to a population)” (Aron A., Aron, E., and Coups, 2011, p. 145). I also learned that hypothesis testing follows a set procedure that appears as follows:
Step 1) Restate the question as a research hypothesis and a null hypothesis about the populations
- Basically, a researcher constructs a hypothesis. Then he/she forms a null hypothesis that opposes the research hypothesis in polar fashion. To help support one’s research hypothesis, one has to disprove the null hypothesis.
Step 2) Determine the characteristics of the comparison distribution
- When using two or more samples, one must gather information about the distribution of means.
Step 3) Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected
- Most researchers choose a significance level of 0.05 or 0.01.
Step 4) Determine your sample’s score on the comparison distribution
Step 5) Decide whether to reject the null hypothesis
(Retrieved from the textbook)
The textbook further introduced me to the notions of one and two-tailed tests, as well as Type I and Type II decision errors, which are highly essential in hypothesis testing.
From the Hypothesis Testing Video, I found out how hypothesis testing is...