Final answer:
The statement that results in statistics are reported with 100% certainty is false. Instead, certainty is expressed through confidence levels, like 90% or 95%, indicating that there's still a chance the true value does not lie within the confidence interval.
Step-by-step explanation:
The statement 'In statistics, results are always reported with 100% certainty' is false. In statistics, certainty is expressed through confidence intervals and probability. For example, a statement like '95 percent of all confidence intervals constructed in this way contain the true value of the population mean statistics exam score' indicates that there is a 5% chance that the true value does not lie within the reported confidence interval. This reflects the inherent uncertainty when estimating population parameters from sample data.
Confidence intervals provide a range of values within which we can say with a certain level of confidence, such as 90% or 95%, that the true population parameter lies. However, this means that there is still a 10% or 5% chance, respectively, that the true parameter does not fall within these intervals. A larger sample size can increase confidence in the results but can never ensure 100% certainty. Comparing the results across repeated experiments or sampling can reinforce our confidence about the estimated parameters, but still does not provide absolute certainty.