Census and Sample Methods in Statistical Investigations

Census Method

Census method is a method of data collection where every item of the universe or population related to the problem under investigation is studied.

Suitability

Census method is particularly suitable for statistical investigations with:

  • Small population size
  • Widely diverse items in the population
  • Requirement of intensive examination of different items
  • High degree of accuracy and reliability needed

Merits

  • Reliable and Accurate: Results are accurate and highly reliable because each item of the population is studied.
  • Less Biased: Results are less biased due to the absence of investigator’s discretion in selecting sample items.
  • Extensive Information: Information collected is exhaustive and meaningful because all items are examined.
  • Study of Diverse Characteristics: Diverse characteristics of the universe can be studied.
  • Study of Complex Investigations: When items are complex and require individual study, only the census method can yield desired results.

Demerits

  • Costly: Census method is expensive and generally not used for ordinary investigations.
  • Large Manpower: Requires a large workforce (enumerators), and training them can be difficult.

Sample Method

Sample method involves collecting data about a sample, a group of items taken from the population, and drawing conclusions based on their analysis.

Merits

  • Economical: Only some units of the population are studied, making it cost-effective.
  • Time Saving: Investigating a limited number of items saves time.
  • Identification of Error: Errors are easily identified due to the limited scope, leading to better accuracy.
  • Large Investigations: More feasible for large investigations compared to the census method, which can be expensive.

Demerits

  • Partial: It’s a partial investigation, and investigator bias in sample selection can lead to biased results.
  • Wrong Conclusions: If the sample doesn’t represent the population’s characteristics, the study may reach incorrect conclusions.
  • Difficulty in Selecting Representative Sample: Selecting a representative sample can be challenging.

Types of Sampling

Random Sampling

Random sampling ensures that each item in the universe has an equal chance of being selected for the sample.

Non-Random Sampling

Non-random sampling includes methods where all population units don’t have an equal probability of being selected.

Merits
  • Allows inclusion of items with special significance.
  • Item selection can be tailored to the study’s purpose.
  • Simple technique for sample selection.
Demerits
  • Possibility of personal bias in item selection.
  • Reliability of results can be questionable due to potential bias.

Difference Between Census and Sample Method

  • Coverage: Census covers all items, while sampling covers a subset.
  • Suitability: Census suits smaller investigations, while sampling is better for larger ones.
  • Accuracy: Census generally yields more accurate results.
  • Cost: Sampling is less expensive.
  • Time: Sampling is less time-consuming.
  • Nature of Items: Census is suitable for populations with diverse characteristics.

Central Problems of an Economy

An economic problem arises from the need to make choices due to scarce resources. It stems from unlimited human desires and limited means to satisfy them.

Production Possibility Curve

In business, a Production Possibility Curve (PPC) helps evaluate a manufacturing system’s performance when producing two commodities together. It aids management in planning the optimal production ratio to minimize waste and costs while maximizing profits.