Students in those preschools could then be selected at random through a systematic method to participate in the study. This does, however, lead to a discussion of biases in research. For example, low-income children may be less likely to be enrolled in preschool and therefore, may be excluded from the study. Extra care has to be taken to control biases when determining sampling techniques. There are two main types of sampling: The difference between the two types is whether or not the sampling selection involves randomization.
Randomization occurs when all members of the sampling frame have an equal opportunity of being selected for the study. Following is a discussion of probability and non-probability sampling and the different types of each.
Probability Sampling — Uses randomization and takes steps to ensure all members of a population have a chance of being selected. There are several variations on this type of sampling and following is a list of ways probability sampling may occur:.
Non-probability Sampling — Does not rely on the use of randomization techniques to select members. This is typically done in studies where randomization is not possible in order to obtain a representative sample.
Bias is more of a concern with this type of sampling. The different types of non-probability sampling are as follows:. The following Slideshare presentation, Sampling in Quantitative and Qualitative Research — A practical how to, offers an overview of sampling methods for quantitative research and contrasts them with qualitative method for further understanding. Examples of Data Collection Methods — Following is a link to a chart of data collection methods that examines types of data collection, advantages and challenges.
Qualitative and Quantitative Data Collection Methods - The link below provides specific example of instruments and methods used to collect quantitative data.
Sampling and Measurement - The link below defines sampling and discusses types of probability and nonprobability sampling. Principles of Sociological Inquiry — Qualitative and Quantitative Methods — The following resources provides a discussion of sampling methods and provides examples. This pin will expire , on Change. This pin never expires. Select an expiration date. About Us Contact Us.
A sample is a part of the population that is subject to research and used to represent the entire population as a whole. What is crucial here is to study a sample that provides a true picture of the whole group. So, only a sample is studied when conducting statistical or marketing research. In simple words, probability sampling also known as random sampling or chance sampling utilizes random sampling techniques and principles to create a sample.
For example, if we have a population of people, each one of the persons has a chance of 1 out of of being chosen for the sample. Types of Probability Sampling Methods. This is the purest and the clearest probability sampling design and strategy.
It is also the most popular way of a selecting a sample because it creates samples that are very highly representative of the population. Simple random is a fully random technique of selecting subjects. All you need to do as a researcher is ensure that all the individuals of the population are on the list and after that randomly select the needed number of subjects.
This process provides very reasonable judgment as you exclude the units coming consecutively. Simple random sampling avoids the issue of consecutive data to occur simultaneously. Then the researcher randomly selects the final items proportionally from the different strata. It means the stratified sampling method is very appropriate when the population is heterogeneous.
Stratified sampling is a valuable type of sampling methods because it captures key population characteristics in the sample. In addition, stratified sampling design leads to increased statistical efficiency.
Thus, with the same size of the sample, greater accuracy can be obtained. This method is appropriate if we have a complete list of sampling subjects arranged in some systematic order such as geographical and alphabetical order. The process of systematic sampling design generally includes first selecting a starting point in the population and then performing subsequent observations by using a constant interval between samples taken. This interval, known as the sampling interval, is calculated by dividing the entire population size by the desired sample size.
For example, if you as a researcher want to create a systematic sample of workers at a corporation with a population of , you would choose every 10th individual from the list of all workers. This is one of the popular types of sampling methods that randomly select members from a list which is too large. A typical example is when a researcher wants to choose individuals from the entire population of the U. It is impossible to get the complete list of every individual.
So, the researcher randomly selects areas such as cities and randomly selects from within those boundaries. Cluster sampling design is used when natural groups occur in a population.
The entire population is subdivided into clusters groups and random samples are then gathered from each group. Cluster sampling is a very typical method for market research. The cluster sampling requires heterogeneity in the clusters and homogeneity between them. Each cluster must be a small representation of the whole population. The key difference between non-probability and probability sampling is that the first one does not include random selection. Non-probability sampling is a group of sampling techniques where the samples are collected in a way that does not give all the units in the population equal chances of being selected.
Probability sampling does not involve random selection at all. Most commonly, the units in a non-probability sample are selected on the basis of their accessibility. They can be also selected by the purposive personal judgment of you as a researcher. Types of Non-Probability Sampling Methods. There are many types of non-probability sampling techniques and designs, but here we will list some of the most popular.
As the name suggests, this method involves collecting units that are the easiest to access: It forms an accidental sample. It is generally known as an unsystematic and careless sampling method. For example, people intercepted on the street, Facebook fans of a brand and etc. This technique is known as one of the easiest, cheapest and least time-consuming types of sampling methods. Quota sampling methodology aims to create a sample where the groups e.
The population is divided into groups also called strata and the samples are gathered from each group to meet a quota. Judgmental sampling is a sampling methodology where the researcher selects the units of the sample based on their knowledge. This type of sampling methods is also famous as purposive sampling or authoritative sampling. In this method, units are selected for the sample on the basis of a professional judgment that the units have the required characteristics to be representatives of the population.
Judgmental sampling design is used mainly when a restricted number of people possess the characteristics of interest.
Snowball sampling isn’t one of the common types of sampling methods but still valuable in certain cases. It is a methodology where researcher recruits other individuals for the study. This method is used only when the population is very hard-to-reach.
Before sampling, the population is divided into characteristics of importance for the research. For example, by gender, social class, education level, religion, etc. Then the population is randomly sampled within each category or stratum.
There are two main types of sampling: probability and non-probability sampling. The difference between the two types is whether or not the sampling selection involves randomization. Randomization occurs when all members of the sampling frame have an equal opportunity of being selected for the study. There are many methods of sampling when doing research. This guide can help you choose which method to use. Simple random sampling is the ideal, but researchers seldom have the luxury of time or money to access the whole population, so many compromises often have to be made.
Social research applications require two essential types of sampling: Probability Sampling: This sampling technique selects random members of a population by setting a few selection criteria. Non-probability Sampling: This sampling method is reliant on a social researcher’s ability to select members and not on a fixed selection. Sampling Methods can be classified into one of two categories: Probability Sampling: Sample has a known probability of being selected. Non-probability Sampling: Sample does not have known probability of being selected as in convenience or voluntary response surveys.