Q: Can you explain p-values and confidence intervals in simple terms?

Definitely. Here you go with simple explanations.

P-value: This indicates the probability that the given result might have occurred accidentally. A low p-value (usually < 0.05) gives stronger evidence against the null hypothesis (which usually would be the case of “no effect” or “no difference”). In other words, when p is smaller, it indicates that the result would be much less likely to occur due to chance.

Confidence Interval (CI): A range of values expected to contain the true value of the population parameter. A 95% confidence interval would mean that we are 95% confident that the real value is somewhere within that interval. The improved precision of the estimate is reflected in the smaller interval.

The two make it possible to appraise your finding’s reliability and significance.