What is the purpose of data sampling in data collection?

To analyze the entire dataset
To collect data from various sources
To select a representative subset
To remove outliers

The correct answer is C. 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, which means that the sample should be similar to the population in terms of the variables being studied.

There are many different sampling methods, and the best method to use depends on the specific research question being asked. Some common sampling methods include simple random sampling, stratified sampling, and cluster sampling.

Data sampling can be used for a variety of purposes, including:

  • To estimate the population mean or proportion
  • To test hypotheses about the population
  • To make predictions about the population
  • To compare two or more populations

Data sampling can be a valuable tool for research, but it is important to use the correct sampling method in order to obtain a representative sample.

Option A is incorrect because data sampling is not used to analyze the entire dataset. Data sampling is used to select a subset of data from the larger dataset.

Option B is incorrect because data sampling is not used to collect data from various sources. Data collection is the process of gathering data from various sources.

Option D is incorrect because data sampling is not used to remove outliers. Outlier removal is the process of identifying and removing data points that are significantly different from the rest of the data.