The sample results provide only what type of values for the population characteristics?

The correct answer, estimates, reflects the nature of statistical sampling and inference. When conducting a sample survey or experiment, the results obtained are based on that specific sample, which may not perfectly represent the entire population. Therefore, the results provide estimates of the population characteristics, such as means or proportions, rather than exact or absolute values.

Estimates are derived through statistical techniques that quantify the uncertainty inherent in sampling. For instance, a sample mean gives a point estimate of the population mean, while confidence intervals can provide a range of values where the true population parameter is likely to fall. This process highlights how sampling introduces variability, meaning the values derived are approximations of the true population characteristics.

In contrast, exact values would imply certainty about the population parameters, which is not achievable through sampling techniques. Absolute values and projected outcomes also suggest a level of certainty or prediction that is not a product of sampling, reinforcing that our statistical findings yield estimates tied to the sampled data rather than definitive truths about the entire population.