In statistics, if you want to increase your confidence level, you should set your P value lower.

• A. True
• B. False
• C. It depends on sample size
• D. It does not affect

Answer: (A)

The main idea here is how the threshold for declaring significance changes the strength of your conclusions. In hypothesis testing, the P value threshold (often called the significance level) is the maximum P value at which you reject the null hypothesis. If you lower that threshold, you require stronger evidence before you decide something is statistically significant. That stronger standard makes you more confident that a declared effect isn’t just due to random variation, effectively increasing the confidence you have in your result. In fact, the complement of that threshold (1 minus alpha) corresponds to the confidence level of the related interval estimate, so lowering the threshold also raises the confidence level of your interval.

Keep in mind this comes with a trade-off: requiring more evidence (lower P value) can reduce your study’s power to detect real effects, potentially needing a larger sample size to maintain the same ability to find true effects.