Final answer:
The statement is true; stratified sampling divides the population into strata and obtains a random sample from each to ensure all subgroups are adequately represented in the study.
Step-by-step explanation:
True: Population is divided into subpopulations (strata) and a random sample is obtained from each strata. This statement describes the process of stratified sampling, which is a method used in statistics to ensure that different subgroups within a population are adequately represented within the sample collected for a survey or study.
Stratified sampling involves first dividing the population into homogeneous groups known as strata. Then, a proportionate simple random sampling is conducted within each stratum to select individuals for the sample. This way, each stratum is represented in the sample, which enhances the validity of the study by reducing sampling bias and improving representativeness. This method contrasts with systematic sampling, where individuals are selected at regular intervals from a list, and cluster sampling, where entire clusters are randomly chosen and all individuals within selected clusters become part of the sample.