Sampling

Sampling

Definition

• Sampling refers to the process of selecting a subset of individuals from within a statistical population to estimate characteristics of the whole population.
• The set of data collected from this step is called a sample.

Types of Sampling

Random Sampling

• Random sampling is a method of selecting n members from a population in such a way that every possible sample of the desired size has the same chance of being chosen.
• The aim is to eliminate bias in the selection process.

Stratified Sampling

• Stratified sampling is a method of sampling that involves dividing a population into subsets, which are called strata.
• The strata are formed based on members’ shared attributes or characteristics.
• A proportionate number of members from each stratum are then selected randomly to form a sample.

Systematic Sampling

• Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval.
• This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size.

Sampling Bias

• Sampling bias occurs when a sample is collected in such a way that some members of the intended population are less likely to be included than others.
• This can affect the validity of the results and conclusions drawn from the study.

Sample Size

• The number of observations in a sample is called the sample size.
• A larger sample size reduces sampling error and increases the precision of the sample estimate.

Sample Error

• Sample error is a measure of statistical variability, indicating to what extent an estimate is likely to range around an unknown population parameter.
• The smaller the sampling error, the more representative the sample will be of the overall population.

Advantages and Disadvantages of Sampling

• Sampling makes it possible to estimate the characteristics of a large population by studying a subset of it, thus making it less time-consuming and cost-effective.
• However, a disadvantage of sampling is that the sample may not fully represent the whole population, leading to errors or bias.

Remember, the key to understanding and using samples effectively is to ensure they are random, sufficient in size, and representative of the population.