Disadvantage of Simple Random Sampling
Not Always Feasible: It can be impractical for very large populations due to time and resource constraints in listing and accessing every member.
Population List Required: A complete and accurate list of the population is needed, which can be difficult to obtain.
Potential for Sampling Error: Random selection might still result in an unrepresentative sample, especially with small sample sizes.
Resource Intensive: It may require significant resources and effort to ensure true randomness and to contact selected individuals.
Difficulty in Subgroup Analysis: It may not adequately capture smaller subgroups within the population, making it challenging to analyze these subgroups separately.
Random Sampling Method
Random Sampling is a method of probability sampling where a researcher randomly chooses a subset of individuals from a larger population. In this method, every individual has the same probability of being selected. The researcher aims to collect data from as large a portion as possible of this randomly chosen subset.
In the field of statistics, sampling serves as the technique for selecting a portion of the population to draw statistical inferences. This subset’s characteristics allow us to estimate the attributes of the entire population. In the realm of market research, sampling methods fall into two primary categories: Random or probability sampling and non-probability sampling.
This article discusses the specific category of probability sampling known as random sampling and its types, formulas, advantages, examples, etc.
Table of Content
- What is Random Sampling?
- Random Sampling Definition
- Types of Random Sampling
- Simple Random Sampling
- Systematic Random Sampling
- Stratified Random Sampling
- Cluster Random Sampling
- How to Perform Simple Random Sampling
- When to Use Random Sampling
- Random Sampling Formula
- Advantages of Simple Random Sampling
- Disadvantage of Simple Random Sampling
- Random Sampling vs Non-Probability Sampling
- Random Sampling Examples
- Practice Questions on Random Sampling
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