Non- probability sampling

PRESENTATION BY:- REHAMAN.M MBA(STUDENT)

Non- probability sampling

Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.

Convenience Sampling:-

Convenience sampling is probably the most common of all sampling techniques. With convenience sampling, the samples are selected because they are accessible to the researcher. Subjects are chosen simply because they are easy to recruit. This technique is considered easiest, cheapest and least time consuming.

Consecutive Sampling:-

Consecutive sampling is very similar to convenience sampling except that it seeks to include all accessible subjects as part of the sample. This non-probability sampling technique can be considered as the best of all non-probability samples because it includes all subjects that are available that makes the sample a better representation of the entire population.

Quota Sampling:- Quota sampling is a sampling methodology wherein data is collected from a homogeneous group. It involves a two-step process where two variables can be used to filter information from the population. It can easily be administered and helps in quick comparison. 

Steps to select Quota sampling1. Divide the population into strata or

groups of individuals that are similar (homogeneous) in some way that is important to the response.

2. Choose a separate sample from each stratum. This does not have to be a random sample

3. Combine these sample to form a Quota sample

Example for Quota sampling

Example: 1- If basis of the quota is college year level and the researcher needs equal representation, with a sample size of 100, he must select 25 1st year students, another 25 2nd year students, 25 3rd year and 25 4th year students. The bases of the quota are usually age, gender, education, race, religion and socioeconomic status.

Example 2- Suppose a researchers is interested in the shopping preference of consumers at a local mall. Since he believes men and women have different preference, the researcher decides to stratify(sub group) the population by gender. From past data, he knows that roughly 60% of mall shoppers are female. He wants a sample size 200. To get a proportional sample, he decide to sample 120 females and 80 males. To save time, he post a sign in the mall to solicit volunteers. He include 120 females volunteers and 80 male volunteers in his sample

Advantages of Quota sampling:-

1. Sample Can be controlled for certain Characteristics

2. Low cost3. Fast4. No sampling Fame

Dis-advantages of Quota sampling:-

1. Not a good representation2. Impossible to assess error3. Biased sample

When to Use Quota Samples?1. it allows the researchers to sample a subgroup that is

of great interest to the study. If a study aims to investigate a trait or a characteristic of a certain subgroup.

2. Researchers can use quota sampling to study a characteristic of a particular subgroup, or observe relationships between different subgroups.

3. Quota sampling can also be used at times when detailed accuracy is not important. 

4. when the company is short of time or the budget of the person who is researching on the topic is limited.

Judgmental Sampling:- Judgmental sampling is more commonly known as purposive sampling. In this type of sampling, subjects are chosen to be part of the sample with a specific purpose in mind. With judgmental sampling, the researcher believes that some subjects are more fit for the research compared to other individuals. This is the reason why they are purposively chosen as subjects.

Snowball Sampling:-

Snowball sampling is usually done when there is a very small population size. In this type of sampling, the researcher asks the initial subject to identify another potential subject who also meets the criteria of the research. The downside of using a snowball sample is that it is hardly representative of the population.

When to Use Non-Probability Sampling

1. This type of sampling can be used when demonstrating that a particular trait exists in the population.

2. It can also be used when the researcher aims to do a qualitative , pilot or exploratory study.

3. It can be used when the research does not aim to generate results that will be used to create generalizations pertaining to the entire population.

4. It is also useful when the researcher has limited budget, time and workforce.

5. It can be used when randomization is impossible like when the population is almost limitless.

6. This technique can also be used in an initial study which will be carried out again using a randomized, probability sampling.

Terminology used in researchSampling Error:- The degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability Sampling Frame:- A listing that should include all those in the population to be sampled and exclude all those who are not in the population 

Sample:- The population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferredSurvey:- A research tool that includes at least one question which is either open-ended or close-ended and employs an oral or written method for asking these questionsControl Group:- The group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.

Controlled Experiment:- An experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two timesPopulation:- The target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.Random Sampling:- A process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance

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