How do you select a random sample from infinite universe/population?
It is impossible to select a random sample from an infinite universe or population, as it would require an infinite amount of time and resources. However, if you have a large but finite population, you can use different sampling techniques to approximate a random sample.
One common technique is using random sampling methods such as simple random sampling, stratified sampling, or cluster sampling. These methods involve randomly selecting individuals or groups from the population to form a representative sample.
Simple random sampling involves assigning a unique identifier or number to each individual in the population and then using a random number generator to select the desired number of individuals.
Stratified sampling involves dividing the population into distinct groups or strata based on certain characteristics, then randomly selecting individuals from each stratum in proportion to their representation in the population.
Cluster sampling involves dividing the population into clusters or groups, randomly selecting some of these clusters, and then including all individuals within the selected clusters in the sample.
It is important to note that even with these techniques, the sample will always be finite and may not fully represent an infinite population accurately. However, these sampling methods can help reduce biases and increase the likelihood of obtaining a representative sample.