Understanding different metrics in population is an essential part of every research group. For this reason, researchers often use sample variance and population variance to analyze different metrics of the data set.
Even though on the surface both of these processes use algebraic computational formulas, but they work on different principles. For this reason, many people get confused with these processes and often interchange one with another.
Sample Variance vs Population Variance
The main difference between Sample Variance and Population Variance is that sample variance is an estimating process by which metrics of any specific sample data can be analyzed & measured through a systematic process and it is often used by various research groups, while population variance is an estimating process by which metrics of any population can be analyzed & measured through a systematic process and it is often used by government agencies.
Comparison Table Between Sample Variance and Population Variance (in Tabular Form)
| Parameter of Comparison | Sample Variance | Population Variance |
|---|---|---|
| What is it | It is an estimating process by which metrics of any specific sample data can be analyzed & measured through a systematic process. | It is an estimating process by which metrics of any population can be analyzed & measured through a systematic process. |
| requirements | Small sample data set. | Large population data set. |
| Used by | Various research groups. | Government agencies. |
| Benefits | It can be done quickly with a limited budget. | Give a reliable conclusion report. |
| Drawback | The reliability of the conclusion report varies from sample to sample. | Takes lots of time and investment for data gathering and analyzing processes. |
What is Sample Variance?
Sample variance is an estimating process by which metrics of any specific sample data can be analyzed & measured through a systematic process. For the analysis process, various algebraic computational formulas are used.
Most sample variance is used to analyze small data sets. Generally, the data set used for the sample variance purposes contains information about fifty to five thousand items. The benefit of the sample variance is that it takes undersized resources to congregate data and analyzing processes. For this reason, it can be done with fewer budgets in a small amount of time.
However, the biggest challenge of the sample variance is the accuracy of the prediction; the analysis report widely depends on the sample size and sample selection process. A large data set provides a more accurate sample variance prediction. On the other hand, the conclusion report of small data sets is less reliable. Similarly, any increase in the data set diversity also increases the reliability of the conclusion report.
Various research groups often use sample variance for their work. For example, many researchers of the medicine production company often use sample variance on a small group of people to see the effectiveness of the medicine. Similarly, many media outlets often use sample variance at the time of the election to forecast the result.
What is Population Variance?
Population variance is an estimating process by which metrics of any population can be analyzed & measured through a systematic process. For the analysis process, a congregation of a large population is required.
Most Population variance is used to analyze large data set. Generally, the data set used for the population variance purposes contains information about millions of items. The benefit of the population variance is that the analysis and forecast results turn out very accurate. Compared to sample variance, this process delivers more accurate predictions.
However, the biggest challenge of the population variance is information gathering. It takes a large investment in the data congregation process for population variance. Along with big-budget, the time required for the population variance analyzing process is much longer.
Due to huge expenses, most small research groups do not always use population variance for their research work. Instead, most government agencies use their budget for collecting data and use Population variance as their analyzing purposes.
Various government agencies use population variance for analyzing census data. It helps them measure different metrics of the public. This information helps them conclude public information. In the future, it helps them in the decision-making process for the government.
Main Differences Between Sample Variance and Population Variance
- On one hand, sample variance is an estimating process by which metrics of any specific sample data can be analyzed & measured through a systematic process. On the other hand, population variance is an estimating process by which metrics of any population can be analyzed & measured through a systematic process.
- The sample variance requires a small sample data set for analyzing processes. It may contain information about fifty to fifty thousand items. However, population variance requires a large data set for analyzing process. It may contain information about millions of people.
- Most of the time, various research groups use sample variance for their research purposes. But most of the time government agencies use population variance to analyze census data.
- The benefit of the sample variance is that it can be done quickly with a limited budget. On the other hand, population variance always gives a reliable conclusion report.
- The drawback of the sample variance is that the reliability of the conclusion report varies from sample to sample, while the drawback of the population variance is that it takes lots of time and investment for data gathering and analyzing process.
Conclusion
Sample variance and population variance are both analyzing systems to understand different metrics in the population. It is not only used by government agencies, but many corporate companies also use them to understand the effectiveness of their product.
Many medical research companies often use sample variance with the advantage of small budget requirements and quick analyzing time. Similarly, many media outlets also use this process during the election exit poll forecast. However, with sample variance, the reliability of the conclusion report always varies from sample to sample.
On the other hand, most government agencies can afford an expensive budget for population variance data collection and analysis process. These agencies analyze public information and help the government formulate productive policies for the public. Due to the large data set, the conclusion report of the population variance is more accurate.
References
- https://link.springer.com/content/pdf/10.1007/BF02065813.pdf
- https://www.jstage.jst.go.jp/article/jmath1948/1/2/1_2_111/_article/-char/ja/