Simple Random Sample
A simple random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group.
Simple Random Sampling
Definition
Simple random sampling refers to a subset of a statistical population in which each member has an equal probability of being chosen. This method ensures that every individual has an equal chance of being selected, thus achieving an unbiased representative sample.
Origin
The concept of simple random sampling originated in the early development stages of statistics, particularly in the 19th and early 20th centuries. As statistical methods evolved, simple random sampling became one of the most fundamental and widely used sampling techniques.
Categories and Characteristics
There are two main forms of simple random sampling: with replacement and without replacement.
- With Replacement: After each selection, the chosen individual is returned to the population, making it possible for that individual to be selected again in subsequent draws. This method is suitable for smaller populations.
- Without Replacement: After each selection, the chosen individual is removed from the population, ensuring that they cannot be selected again. This method is more common as it avoids duplicate sampling.
Specific Cases
Case 1: Suppose a class has 30 students, and a teacher wants to randomly select 5 students for a survey. Using simple random sampling, the teacher can write each student's name on a piece of paper, place them in a box, and randomly draw 5 pieces of paper. This way, each student has an equal probability of being selected.
Case 2: In market research, researchers want to randomly select 100 customers from a database of 1,000 customers for a satisfaction survey. Researchers can use a computer-generated random number to select these 100 customers, ensuring that each customer has an equal probability of being chosen.
Common Questions
Question 1: Is simple random sampling always the best sampling method?
Answer: Not necessarily. While simple random sampling is the most basic method, other sampling methods (such as stratified sampling or systematic sampling) may be more suitable in certain situations.
Question 2: How can we ensure the sampling process is truly random?
Answer: Using random number generators or other randomization tools can ensure the randomness of the sampling process, avoiding human intervention.
