Final answer:
Statistical sampling is a practical method that is most accurately described as reliable and objective for estimating the value of an auto dealer's large inventory, as long as the sampling method provides a representative subset of the population.
Step-by-step explanation:
Statistical sampling is a technique often used when it is impractical or too expensive to study a whole population. It involves selecting a subset of the population which has the same characteristics as the entire population to make inferences about the population. For an auto dealer's 3,000 line-item inventory, statistical sampling is most accurately described as reliable and objective (option 3). The effectiveness of the sampling method depends on the sample being representative of the entire population, and random sampling methods, such as simple random sampling and probability sampling, are designed to achieve this representation. Sampling can produce reliable estimates if proper techniques are used, even with a relatively small sample compared to the population, due to the law of large numbers and central limit theorem.
The accuracy of the estimates from sampling can be compromised by factors such as sampling bias or too small sample sizes, but these can be mitigated by employing appropriate sampling methods and ensuring the sample is large enough. Statisticians use tools such as confidence intervals and hypothesis testing to quantify the reliability and objectiveness of the sample estimate.