What type of sample selects individuals randomly from a larger group?

A random sample is one in which individuals are selected from a larger group entirely by chance, ensuring that every member of the population has an equal opportunity to be chosen. This method is fundamental in statistics because it helps eliminate biases and allows for the generalization of results to the broader population. The randomness of selection is key to ensuring that the sample reflects the diversity of the larger group, which enhances the validity of any conclusions drawn from the data.

In contrast, the other sampling methods have different characteristics that make them less suited for random selection. A stratified sample divides the population into distinct subgroups or strata, and selects randomly from each subgroup, which is not purely random as it involves additional consideration of the strata. A systematic sample involves selecting individuals based on a fixed, predetermined interval, which introduces a systematic pattern rather than a random choice. A convenience sample entails selecting individuals based on their availability and willingness to participate, which can lead to a biased representation of the population. Each of these methods serves specific research purposes but does not embody the true randomness that characterizes a random sample.