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Population, Sample & Types

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🌍 Population (N)

  • Definition: The complete set of individuals, items, or data points relevant to a study.
  • Examples in Biostatistics:
  • All patients with diabetes in Pakistan.
  • Every newborn in a hospital during one year.

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đź‘Ą Sample (n)

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  • Definition: A smaller, manageable group selected from the population.

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  • Purpose: To make inferences about the population without studying everyone.

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  • Examples:

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  • 200 diabetic patients randomly chosen from Karachi hospitals.

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  • 50 newborns selected from a maternity ward

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🎯 Sampling

  • Definition: The process of selecting a sample from the population.
  • Goal: To ensure the sample represents the population accurately, minimizing bias.
  • Importance in Biostatistics:
  • Reduces cost and effort.
  • Allows statistical inference.
  • Ensures validity of research findings.

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What is Probability Sampling?

  • The probability sampling method utilizes some form of random selection.
  • In this method, all the eligible individuals have a chance of selecting the sample from the whole sample space.

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Simple Random Sampling

  • In simple random sampling technique, every item in the population has an equal and likely chance of being selected in the sample. Since the item selection entirely depends on the chance, this method is known as “Method of chance Selection”. As the sample size is large, and the item is chosen randomly, it is known as

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Systematic Sampling

  • In the systematic sampling method, the items are selected from the target population by selecting the random selection point and selecting the other methods after a fixed sample interval. It is calculated by dividing the total population size by the desired population size.

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Stratified Sampling

  • In a stratified sampling method, the total population is divided into smaller groups to complete the sampling process. The small group is formed based on a few characteristics in the population. After separating the population into a smaller group, the statisticians randomly select the sample.

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Clustered Sampling

  • In the clustered sampling method, the cluster or group of people are formed from the population set.
  • The group has similar significatory characteristics. Also, they have an equal chance of being a part of the sample. This method uses simple random sampling for the cluster of population.

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What is Non-Probability Sampling?

  • The non-probability sampling method is a technique in which the researcher selects the sample based on subjective judgment rather than the random selection.
  • In this method, not all the members of the population have a chance to participate in the study.

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Convenience Sampling

  • In a convenience sampling method, the samples are selected from the population directly because they are conveniently available for the researcher.
  • The samples are easy to select, and the researcher did not choose the sample that outlines the entire population

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Quota Sampling

  • In the quota sampling method, the researcher forms a sample that involves the individuals to represent the population based on specific traits or qualities.
  • The researcher chooses the sample subsets that bring the useful collection of data that generalizes the entire population

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Purposive or Judgmental Sampling

  • In purposive sampling, the samples are selected only based on the researcher’s knowledge.
  • As their knowledge is instrumental in creating the samples, there are the chances of obtaining highly accurate answers with a minimum marginal error.
  • It is also known as judgmental sampling or authoritative sampling

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Snowball Sampling

  • Snowball sampling is also known as a chain-referral sampling technique.
  • In this method, the samples have traits that are difficult to find. So, each identified member of a population is asked to find the other sampling units. Those sampling units also belong to the same targeted population.

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Probability Sampling Methods

Non-probability Sampling Methods

Probability Sampling is a sampling technique in which samples taken from a larger population are chosen based on probability theory.

Non-probability sampling method is a technique in which the researcher chooses samples based on subjective judgment, preferably random selection.

These are also known as Random sampling methods.

These are also called non-random sampling methods.

These are used for research which is conclusive.

These are used for research which is exploratory.

These involve a long time to get the data.

These are easy ways to collect the data quickly.

There is an underlying hypothesis in probability sampling before the study starts. Also, the objective of this method is to validate the defined hypothesis.

The hypothesis is derived later by conducting the research study in the case of non-probability sampling.