Non Probability Sampling and Probabilistic Methods

NON PROBABILITY SAMPLING

DEFINITION

Non-probability sampling is a sampling technique in which the researcher selects samples based on the subjective judgement of the researcher rather than random selection.

In non-probability sampling, not all members of the population have a chance of participating in the study unlike probability sampling, where each member of the population has a known chance of being selected.

This method is commonly used in studies where it is not possible to draw random sampling due to time or cost considerations.

This method is less stringent as it depends heavily on expertise of the researcher. It is carried out through methods of observation and is widely used in qualitative research.

Types of non-probability sampling

I. Convenience sampling.

This is non-probability sampling method where samples are selected only because they are easy to recruit and researcher did not consider selecting sample that represents the entire population

Ideally, due to population been too large to test and consider the entire population these stimulate the researcher to rely on convenience method.

The method is common as it’s; speed, cost-effectiveness and ease of availability of the sample.

Example; using students volunteer known to researcher. Researcher can send the survey to student and they would act as sample in this situation.

II. Consecutive sampling.

In this technique the researcher picks a single person or group of sample, conducts research over a period of time, analyzes the results and moves on to another subject or group of subject if needed.

It gives a researcher a chance to work with many subjects and fine tune his/her research by collecting results that have vital insights

III. Judgmental or purposive sampling.

In judgmental sampling, the samples are selected based purely on researcher’s knowledge and credibility. In other words, researchers choose only those who he feels are right fit (with respect to attributes and representation of population) to participate in researcher study.

There is high ambiguity involved in this research technique as its results can be influenced by the preconceived notions of the researcher.

IV. Snowball sampling

Snowball sampling helps researchers find sample when they are difficult to locate. Researchers use this method when the sample size is small and not easily available. This sampling sample works like the referral program. Once the researchers find suitable subjects, they are asked for assistance to seek similar subjects to form a considerably good size sample.

Example; this type of sampling can be used to conduct research involving particular illness in patients or a rare disease. Researchers can seek help from subjects to refer other subjects suffering from the same ailment to form a subjective sample to carry out the study.

V. Quota sampling

This method helps researcher to divide population into strata or groups.

Example; when studying the career goals of 500 employees, technically the sample selected should have proportionate numbers of male and females. Which means there should be 250 males and 250 females. Since this is unlikely, the groups or strata is selected using quota sampling.

When to use non-probability sampling?

• This type of sampling is used to indicate if a particular trait or characteristic exists in a population.

• The technique is used when researchers aim at conducting qualitative research, or expository research.

• It is conducted to observe if a particular issue needs in – depth analysis

Advantages of non-probability.

1. Non-probability sampling is more conducive and practical method for researchers deploying survey in the real world.

2. Getting responses using non-probability sampling is faster and more cost-effective as compared to probability sampling because sample is known to researcher, they are motivated to respond quickly as compared to people who are randomly selected.

Disadvantage of non-probability sampling.

• in non-probability sampling, researchers need to think through potential reasons for biases. It is important to have a sample that represents closely the population.

• While choosing a sample in non-probability sampling, researchers need to be careful about the recruits distorting data. At the end of day, research is carried out to obtain meaningful insights and useful data.

QUESTIONARRE

DEMONSTRATIONAL STRIKES VERSUS THE PEOPLE’S WELFARE.

GAP: EFFECTS OF DEMOSTRATIONS AND STRIKES TO PEOPLE’S WELFARE

Open ended question

1. Have you ever participated in demonstrations and strikes?

2. If yes, what do you think are major causes of strikes?

3. Are demonstrations and