Answer:
a. stratified
Step-by-step explanation:
Let us look at the definition of all options first.
a. stratified
In stratified sampling the population is divided into groups based on some characteristics and then the sample is chosen randomly from the groups also called strata.
b. cluster
In cluster sampling, every member of the population is assigned to only one group. Group is called cluster. The sample is then chosen from the clusters using probability sampling.
c. random
In random sampling every member of the population has equal chance of being selected in the sample.
d. convenience
The sample is selected based on their accessibility to the researcher
e. systematic
In systematic sampling, the sample is chosen from the population by choosing a random starting point and then moving forward with the same periodic interval. The period is calculated by dividing the population size by the size of desired sample size.
After going through all the definitions, it can be concluded that choosing Thirty-five sophomores, 30 juniors and 33 seniors randomly from 281 sophomores, 242 juniors and 529 seniors at a certain high school is stratified sampling as the groups are divided based on their year in high school and then the sample is randomly chosen among them ..