Which characteristic defines a Statistical Valid Sample?

A Statistical Valid Sample is defined by its random selection process. This characteristic ensures that each item in the population has an equal chance of being selected, thus eliminating any biases that might skew the results. When samples are chosen randomly, the findings can be generalized to the larger population with a greater degree of accuracy, making them more reliable for statistical analysis.

In contrast, options that involve biases or non-random selection methods compromise the validity of the sample. If a sample includes all items in the universe, it would represent a complete census rather than a sample, which is an entirely different methodology. Similarly, biased selection based on convenience or judgment undermines the fundamental principle of statistical sampling, as it could lead to results that are not representative of the broader population. Therefore, random selection is essential for ensuring the statistical validity of a sample.