Haphazard Sampling

What Is Haphazard Sampling?

Haphazard Sampling refers to the unsystematic selection of samples from a population for study and analysis. In this approach, the examiner or analyst does not follow or look for any structure, difference, conditions, or quality. Many cases exist when such a sample is taken from a large population.

Since no particular guideline is followed, the results of haphazard sampling methods typically have a degree of inaccuracy and skepticism. However, the degree of skepticism varies depending on the study the examiner is pursuing. When resources or time are limited, this approach in business and finance can provide quick assessments or preliminary insights. However, its unsystematic character may not yield accurate results. Hence, it is essential to confirm the results through more robust sample approaches.

• Haphazard sampling is a data selection technique that follows no standard rule, guideline, or structure.
• It is well known for ambiguous results, a higher degree of inaccuracy, ill-treated data, and skepticism.
• The use of this approach may lead to doubts about the reliability of the researcher's work due to potential biases and concerns about data accuracy.
• Unlike random sampling, which ensures that each element has an equal probability of being selected, this method is not as uniform and could induce bias.

Haphazard Sampling Explained

Haphazard sampling refers to the selection of a data sample with no regard for rules, standards, or systematic approach. It is common when taking general public views and performing street surveys. While it is highly unbiased, it covers information from irrelevant elements. As a result, it can be confusing and complex and often does not offer reliable results.

Like every sampling method, the haphazard sampling technique also has limitations and, therefore, cannot be used in every type of research. A persistent problem with such a type of sampling is that it not only chooses random people but caters to a wide range of audiences with no relevance or connection to the study. Moreover, this sampling method is frequently performed in haste when people are not interested in answering the questions or becoming a sample element.

A researcher may have to apply multiple sampling techniques to ensure that the data they are collecting is relevant and correct and will offer useful insights. However, crucial factors influencing data collection and analysis are often overlooked in haphazard sampling. The sampling does not consider any assumptions and individual opinions. Despite its limitations, analysts may pursue such a sampling technique on a low budget or work to represent a basic statistical figure.

Examples

Let us consider these examples to understand the concept better:

Example #1

Suppose Terry goes to school in New York. He receives an assignment in his class to discover how many people play video games in their free time. Terry decides to visit Times Square, one of the busiest areas and a prominent entertainment hub of New York, to collect data for his assignment.

He reaches there by early evening and starts asking walkers and street crossers at random about their video game experience. Terry happens to interview anyone walking by and has yet to have an intention or proper plan as to why he selected them. He stays there late until 9 pm and manages to interview almost 180 citizens walking by Times Square. He collects their responses and submits his results.  

Example #2

A side event was held in July 2019 during the 25th Session of the International Seabed Authority. Researchers talked about biodiversity assessment at Seafloor Massive Sulphides (SMS) sites. They employed haphazard sampling technique because of deep-sea exploration's unexpected nature and practical limitations.

Using remotely operated vehicles or submersibles, they resourcefully gathered samples from regions where SMS colonies were detected. Although it lacked systematic accuracy, this sampling method highlighted the adaptability of scientific inquiry in difficult situations. Moreover, it offered insightful information about SMS biodiversity across several biogeographic provinces.

Advantages And Disadvantages

Listed below are the advantages and disadvantages of this sampling technique:

Advantages:

• The sampling method is cost-effective compared to other methods.
• It offers a result when there is no need for more resources, standardization, and access to software and intelligence.
• Provides an unbiased view of people’s opinions.

Disadvantages:

• The research and sampling can be suspected of being biased easily.
• There is an equal chance that the results may be inaccurate and not true to the nature of the study.
• The method has no guaranteed precision or representative foundation.
• Certain people from certain locations may respond in unison to the research.
• The outcome of such studies often exhibits randomness.

Haphazard Sampling vs Random Sampling

The differences between the two sampling methods are given below:

Aspect	Haphazard Sampling	Random Sampling
Structure/Standard of Sampling	This approach does not follow any structure or standard of sampling.	Random sampling is performed under the sampling rules.
Equal Chance of Selection	In this method, no element of the sample is offered an equal chance of selection	This sampling method allows every sample element to be selected.
Selection Criteria	In this technique, the researcher or analyst chooses anyone walking on the company floor	In random sampling, the researcher or analyst opts out of people working there

Frequently Asked Questions (FAQs)

Recommended Articles

This article has been a guide to what is Haphazard Sampling. Here, we explain its examples, differences with random sampling, advantages, & disadvantages. You may also have a look at these recommended corporate finance articles –

• Random Sampling
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