The Difference Between Population and Sample
When conducting research or gathering data, it’s crucial to understand the difference between population and sample. Both terms are used to describe groups of people, objects, or events, but they serve different purposes and require different methods of analysis.
Population
A population refers to the entire group of people, objects, or events that you’re interested in studying. For example, if you want to know the average income of all the residents in a city, the population would be all residents of that city.
A population can be finite or infinite, depending on the size of the group. If you’re studying a small group of people, such as the employees of a company, the population is finite. If you’re studying a larger group, such as all the residents of a country, the population is infinite.
When studying a population, researchers generally try to measure or observe every individual in the group. This requires a large amount of time, resources, and effort. However, analyzing data from a population can provide highly accurate results.
Sample
A sample, on the other hand, is a smaller group of people, objects, or events that represent the larger population. For example, if you’re interested in knowing the average income of all the residents in a city, you might take a sample of 1,000 residents and use their data to make an estimate for the entire population.
When selecting a sample, researchers use various methods to ensure it’s representative of the population. This includes random sampling, where individuals are selected at random, and stratified sampling, where the population is divided into subgroups and individuals are selected from each subgroup in proportion to their representation in the population.
Analyzing data from a sample is less costly and time-consuming than analyzing data from the entire population. However, the results may be less accurate because of sampling errors or biases.
Conclusion
In summary, population and sample are two terms used in research and data analysis that refer to different groups of people, objects, or events. Population refers to the entire group being studied, while a sample is a smaller subset of that group. While analyzing data from a population can provide highly accurate results, it’s generally not practical or feasible. Analyzing data from a sample is a more common and cost-effective method, but care must be taken to select a representative sample to ensure accurate results.
Table difference between population and sample
| Population | Sample | |
|---|---|---|
| Definition | The entire group that a researcher is interested in studying | A subset of the population that a researcher selects to study |
| Size | Larger | Smaller |
| Characteristics | Comprised of all individuals or units that share a common characteristic | Representative of the population, but only includes a portion of individuals or units that share a common characteristic |
| Cost and Time | More costly in terms of money, time, and resources | Less costly in terms of money, time, and resources |
| Generalization | Findings can be generalized to the entire population | Findings can only be generalized to the sample |
| Accuracy | Potentially more accurate due to larger sample size and scope | Potentially less accurate due to smaller sample size and scope |