Final answer:
To increase statistical power, researchers should increase the sample size, which decreases the probability of a Type II error and makes it more likely to detect true effects.
Step-by-step explanation:
One way to increase statistical power in our research is to increase the sample size, which can increase the Power of the Test. The power of a statistical test, represented as 1 − β, is the probability that the test correctly rejects the null hypothesis when a real effect exists. High power is desirable, and a larger sample size usually leads to a narrower confidence interval, decreasing the likelihood of a Type II error (β error).
It's important to note that increasing the effect size or decreasing the probability of a Type II error (β) could also increase the power of a test. However, choosing the correct method depends on the specific context of the research. In contrast, decreasing the sample size or increasing the β (type-II error) level would decrease the power of the test, making it less likely to detect true effects.