The correct answer is: B. To select a representative subset.
Data sampling is the process of selecting a subset of data from a larger population. The goal of data sampling is to obtain a representative sample of the population that can be used to make inferences about the population as a whole.
There are many different sampling methods, each with its own advantages and disadvantages. The choice of sampling method depends on the specific research question being asked and the characteristics of the population.
Some common sampling methods include:
- Simple random sampling: Each member of the population has an equal chance of being selected.
- Stratified sampling: The population is divided into groups (strata) and a random sample is selected from each group.
- Cluster sampling: The population is divided into clusters and a random sample of clusters is selected.
- Systematic sampling: Every nth member of the population is selected.
Data sampling can be a powerful tool for data analysis. However, it is important to use a sampling method that is appropriate for the research question and the population. Otherwise, the results of the analysis may not be representative of the population as a whole.
Here are some brief explanations of the other options:
- A. To analyze the entire dataset: This is not the purpose of data sampling. Data sampling is used to select a subset of data from a larger population. The entire dataset is not analyzed.
- C. To visualize data: Data visualization is a tool that can be used to present data in a way that is easy to understand. However, data visualization is not the purpose of data sampling.
- D. To calculate data statistics: Data statistics can be calculated from a sample of data. However, data statistics are not the purpose of data sampling.