Ways of selecting samples

1. Probability Sampling Methods
Samples are selected in such a way that each item or person in the population has a known (Nonzero) likelihood of being included in the sample.

Types of Probability sampling methods
a) Simple Random Sampling:
A sample is selected so that each item or person in the population has the same chance of being included.
Advantages
• Easy to implement with automatic dialing and with computerized voice response systems.
Disadvantages
• Requires a listing of population elements.
• Takes more time to implement
• Uses larger sample sizes
• Produces larger errors
• Expensive
b) Systematic Random Sampling:
The items or individuals of the population are arranged in some manner. A random starting point is selected and then every kth member of the population is selected for the sample.
Advantages
1. Simple to design
2. Easier to use than the simple random.
3. Easy to determine sampling distribution of mean or proportion.
4. Less expensive than simple random.
Disadvantages
? Periodicity within the population may skew the sample and results.
? If the population list has a monotonic trend, a biased estimate will result based on the start point.
c) Stratified Random Sampling:
A population is divided into subgroups called strata and a sample is selected from each stratum. After the population is divided into strata, either a proportional or a non-proportional sample can be selected. In a proportional sample, the number of items in each stratum is in the same proportion as in the population while in a non-proportional sample, the number of items chosen in each stratum is disproportionate to the respective numbers in the population.
Advantages
• Researcher controls sample size in strata
• Increased statistical efficiency
• Provides data to represent and analyze subgroups.
• Enables use of different methods in strata.

Disadvantages
• Increased error will result if subgroups are selected at different rates
• Expensive especially if strata on the population have to be created.

d) Cluster Sampling:
The population is divided into internally heterogeneous subgroups and some are randomly selected for further study. It is used when it is not possible to obtain a sampling frame because the population is either very large or scattered over a large geographical area. A multi-stage cluster sampling method can also be used.
Advantages
• Provides an unbiased estimate of population parameters if properly done.
• Economically more efficient than simple random.
• Lowest cost per sample, especially with geographic clusters.
• Easy to do without a population list.

Disadvantages
• More error (Lower statistical efficiency) due to subgroups being homogeneous rather the heterogeneous.

2. Non - Probability Sampling Methods
It is used when a researcher is not interested in selecting a sample that is representative of the population.
a) Convenience or Accidental Sampling
It involves selecting cases or units of observation as they become available to the researcher e.g. asking a question to the radio listeners, roommates or neighbours.
b) Purposive Sampling: There are two main types; judgmental and quota
i. Judgement Sampling: Occurs when a researcher selects sample members to conform to some criterion. It allows the researcher to use cases that have the required information with respect to the objectives of his or her study e.g. educational level, age group, religious sect etc.
ii. Quota Sampling
The researcher purposively selects subjects to fit the quotas identified e.g.
• Gender: Male or Female.
• Class Level: Graduate or Undergraduate
• School: Humanities, Science or human resource development.
• Religion: Muslim, Protestant, catholic, Jewish.
• Fraternal affiliation: member or nonmember.
• Social economic class: Upper, middle or lower.

Advantage
Widely used by pollsters, marketers and other researchers.
Disadvantages
• It gives no assurance that the sample is representative of the variables being studied.
• The data used to provide controls may be outdated or inaccurate.
• There is a practical limit on the number of simultaneous controls that can be applied to ensure precision.
• Since the choice of subjects is left to field workers, they may choose only friendly looking people.

c) Snow ball sampling
It is used when the population that possesses the characteristics under study is not well known and can be best located through referral networks. Initial subjects are identified who in turn identify others. Commonly used in drug cultures, teenage gang activities, Mungiki sect, insider trading, Mau Mau etc.

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Titany answered the question on October 21, 2021 at 12:45