A term refers to the technique where each member of the popuation has an equal chnace of being selected. It is the most unbiased method of sampling.

• Stratified sampling

• Systematic sampling

• Simple random sampling

• Purposive sampling

Answer explanation

Simple random sampling is the technique where each member of the population has an equal chance of being selected, making it the most unbiased method of sampling compared to other methods like stratified or purposive sampling.

It is a random sampling technique which considers every nth element of the population in the sample.

• Stratified sampling

• Systematic sampling

• Simple random sampling

• Cluster sampling

Answer explanation

Systematic sampling involves selecting every nth element from the population, making it distinct from other methods like stratified or cluster sampling, which use different criteria for selection.

This type of probability sampling refers to the population that was being divided into groups called clusters.

• stratified sampling

• Cluster sampling

• Simple random sampling

• Systematic random sampling

Answer explanation

Cluster sampling involves dividing the population into groups, or clusters, and then randomly selecting entire clusters for the sample. This distinguishes it from other sampling methods like stratified or simple random sampling.

This type of sampling technique is also called as haphazard sampling. Implies that this sampling procedure is carried out on the matter of convenience or ease of implementation.

• Conveniece Sampling

• Purposive Sampling

• Snowball sampling

• Quota Sampling

Answer explanation

Convenience sampling, also known as haphazard sampling, is a method where samples are selected based on ease of access and convenience, making it the correct choice for this question.

This sampling technique is done with a purpose in mind and also called as judgemental or selective sampling.

• Quota sampling

• Snowball sampling

• Convenience sampling

• Purposive sampling

Answer explanation

Purposive sampling, also known as judgemental or selective sampling, is a technique where participants are selected based on specific characteristics or criteria, aligning with the purpose of the study.

This sampling technique is sometimes called as chain-referral sampling. The researcher chooses a possible respondent for the study at hand.

• Purposive sampling

• Quota sampling

• Convenience sampling

• Snowball sampling

Answer explanation

Snowball sampling, also known as chain-referral sampling, involves selecting respondents who then refer others, creating a 'snowball' effect. This technique is useful for reaching hard-to-find populations.

It is the equivalent of stratified random sampling in terms of nonprobability sampling. Researchers starts identifying quotas, which are predefined control categories such as age, gender, education, or religion.

• Convenience sampling

• Purposive sampling

• Quota sampling

• Snowball sampling

Answer explanation

Quota sampling is the correct choice as it involves setting predefined categories like age or gender to ensure representation, similar to stratified random sampling but without random selection.

The term pertains to the totality of obeservations or elements from a set of data.

• data statistics

• population

• sample

• parameter

Answer explanation

The term 'population' refers to the entire set of observations or elements from which data is collected, making it the correct choice. In contrast, 'sample' refers to a subset of the population.

One or more elements taken from the population for specific purpose.

• Sample

• Population standard deviation

• parameter

• statistics

Answer explanation

A 'Sample' refers to one or more elements taken from a population for a specific purpose, making it the correct choice. Other options like 'parameter' and 'statistics' do not fit this definition.

It refers to the numerical description of the sample.

• Statistic

• Parameter

• Population

• Sample

Answer explanation

A statistic is a numerical description derived from a sample, while a parameter refers to a characteristic of a population. Therefore, the correct answer is 'Statistic'.