Table of Contents
Sample Size And Sampling Techniques In Research
The term “sample size” usually refers to the number of items or individuals in a sample. In most cases, the larger the sample size, the more accurate the estimate of the population parameter. There are a variety of sampling techniques that can be used to select a sample. The most common sampling techniques are simple random sampling, stratified sampling, and cluster sampling.
Simple random sampling is a technique in which every item in the population has an equal chance of being selected. Stratified sampling is a technique in which the population is divided into strata, and a sample is selected from each stratum. Cluster sampling is a technique in which the population is divided into clusters, and a sample is selected from each cluster.
| S.NO | CONTENT |
| 1. | INTRODUCTION |
| 2. | TYPES OF SAMPLING |
| 3. | PROBABILITY SAMPLING |
| 4. | TYPES OF PROBABILITY SAMPLING |
| 5. | NON PROBABILITY SAMPLING |
| 6. | TYPES OF NON-PROBABILITY SAMPLING |
| 7. | FAQ’S |
Types Of Sampling Methods
There are three types of sampling methods:
1. Probability sampling
2. Non-probability sampling
3. Quota sampling
Probability Sampling
Probability sampling is a method of selecting a sample from a population in such a way that each member of the population has a known chance of being selected. There are many different types of probability sampling, but they all share a common feature: each member of the population has a known chance of being included in the sample. This feature is what makes probability sampling different from other types of sampling, like convenience sampling or snowball sampling.
There are several different types of probability sampling. The most common are simple random sampling, stratified sampling, and cluster sampling.
In simple random sampling, every member of the population has an equal chance of being selected. This type of sampling is often used when the population is large and the researcher wants to ensure that every member of the population has an equal chance of being included in the sample.
In stratified sampling, the population is divided into strata, or groups, and a random sample is selected from each stratum. This type of sampling is often used when the population is heterogeneous, or diverse, and the researcher wants to ensure that each group in the population is represented in the sample.
In cluster sampling, the population is divided into clusters, or groups, and a random sample is selected from each cluster. This type of sampling is often used when the population is large and the researcher wants to reduce the cost and time required to select a sample.
Types Of Probability Sampling With Examples:
There are many types of probability sampling. Here are a few examples:
1. Simple Random Sampling: This is the most basic type of probability sampling. It involves randomly selecting participants from the population. This can be done with a random number generator or by using a sampling frame.
2. Stratified Sampling: This type of sampling involves dividing the population into strata and selecting participants from each stratum randomly. This is often used when there is a need to ensure that the sample is representative of the population.
3. Cluster Sampling: Cluster sampling involves selecting clusters of participants from the population. The clusters are then randomly sampled. This type of sampling is often used when the population is too large to sample randomly.
4. Systematic Sampling: Systematic sampling involves selecting participants from the population in a systematic way. This type of sampling is often used when the population is too large to sample randomly.
Non-probability Sampling
Non-probability sampling is a type of sampling that does not use a random process to select participants. This type of sampling can be done in a number of different ways, including using convenience sampling, quota sampling, or snowball sampling.
Non-probability sampling is often used when doing research because it is easier and quicker to do than probability sampling. However, it is important to note that because non-probability sampling is not random, it can lead to biased results.
Types Of Non-probability Sampling With Examples
There are many types of non-probability sampling techniques. Some of the most common are as follows:
1. Convenience Sampling: This technique is used when the researcher wants to study a specific population that is easily accessible. For example, a researcher may want to study the attitudes of college students on a particular issue. To do this, the researcher would recruit participants from among the students who are easily accessible, such as those who are on campus on the day of the study.
2. Snowball Sampling: This technique is used when the researcher wants to study a population that is difficult to access. For example, a researcher may want to study the attitudes of homeless people on a particular issue. To do this, the researcher would ask some homeless people about their opinions on the issue, and then ask those people who they know about the issue. This process would continue until the researcher has studied the opinions of a representative sample of the population.
3. Quota Sampling: This technique is used when the researcher wants to study a specific population but does not have access to a list of all the members of that population. For example, a researcher may want to study the opinions of registered voters on a particular issue. To do this, the researcher would recruit participants until they had studied the opinions of a representative sample of registered voters.
4. Purposive Sampling: This technique is used when the researcher has a specific population in mind that they want to study, but
Practice Problem
1. In the figure below, a prism is shown with two different types of light incident on its surface. The angle of incidence of the first type of light is θ1, and the angle of incidence of the second type of light is θ2. Which type of light is reflected more by the prism?
The light that is reflected more by the prism is the light that has the smaller angle of incidence, θ2.
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