What is implied if the confidence interval indicates the true effect of treatment lies within a specific range?

When a confidence interval indicates that the true effect of a treatment lies within a specific range, it suggests that the treatment has a real and measurable impact, assuming the range does not include zero. In statistical terms, if the confidence interval does not encompass zero, it implies that there is a statistically significant effect of the treatment being studied; therefore, the true effect is likely not zero.

This interpretation stems from the concept that a confidence interval gives a range of values that, based on the sample data, is believed to contain the true population parameter (in this case, the treatment effect) with a certain level of confidence (commonly 95%). If the interval excludes zero, it's an indication that the treatment is likely to produce an effect different from no effect at all. This is a fundamental principle in statistics, emphasizing the relationship between the confidence interval and the significance of treatment effects.

Understanding this helps in recognizing how to interpret findings in clinical research or data analysis, where establishing whether a treatment has a true effect is crucial for drawing meaningful conclusions.