It is not possible for researchers to collect data from everyone in a sample area or community. Therefore, the researcher must gather data from a sample, or subset, of the population in the study.
In quantitative research, the goal would be to conduct a random sampling that ensured the sample group would be representative of the entire population, and therefore, the results could be generalized to the entire population.
The goal of qualitative research is to provide in-depth understanding and therefore, targets a specific group, type of individual, event or process. To accomplish this goal, qualitative research focus on criterion-based sampling techniques to reach their target group. There are three main types of qualitative sampling: The following descriptions describe the reasons for choosing a particular method. A note on sample size - Once a sampling method has been determined, the researcher must consider the sample size.
In qualitative studies, sampling typically continues until information redundancy or saturation occurs. This is the point at which no new information is emerging in the data. Therefore, in qualitative studies is it critical that data collection and analysis are occurring simultaneously so that the researcher will know when the saturation point is reached. It is important to understand that the saturation point may occur prematurely if the researcher has a narrow sampling frame, a skewed analysis of the data, or poor methodology.
Because of this, the researcher must carefully create the research question, select an appropriate target group, eliminate his or her own biases and analyze data continuously and thoroughly throughout the process to bring validity to the data collected. The following slideshare presentation, Collecting Qualitative Data , and the Resource Links on this page provide additional insight into qualitative sampling. Qualitative Research Methods - A Data Collectors Field Guide - This comprehensive, detailed guide describes various types of sampling techniques and provides examples of each, as well as pros and cons.
Qualitative Research Overview - The following link provides a full overview of qualitative research, but also contains sections discussing types of sampling methods and methods of participant recruitment. Sampling - This resource provides a brief overview of sampling and sample size with links to descriptions of purposeful sampling strategies. 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. We all need to remember that public opinion on a given topic cannot be appropriately measured with one question that is only asked on one poll. Such results only provide a snapshot at that moment under certain conditions.
The concept of repeating procedures over different conditions and times leads to more valuable and durable results. Within this section of the Gallup article, there is also an error: In 5 of those surveys, the confidence interval would not contain the population percent.
Eberly College of Science. Printer-friendly version Sampling Methods can be classified into one of two categories: 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 Probability Sampling In probability sampling it is possible to both determine which sampling units belong to which sample and the probability that each sample will be selected.
Simple Random Sampling SRS Stratified Sampling Cluster Sampling Systematic Sampling Multistage Sampling in which some of the methods above are combined in stages Of the five methods listed above, students have the most trouble distinguishing between stratified sampling and cluster sampling.
With stratified sampling one should: With cluster sampling one should divide the population into groups clusters. Stratified sampling would be preferred over cluster sampling, particularly if the questions of interest are affected by time zone. For example the percentage of people watching a live sporting event on television might be highly affected by the time zone they are in.
Cluster sampling really works best when there are a reasonable number of clusters relative to the entire population. In this case, selecting 2 clusters from 4 possible clusters really does not provide much advantage over simple random sampling.
Either stratified sampling or cluster sampling could be used. It would depend on what questions are being asked. For instance, consider the question "Do you agree or disagree that you receive adequate attention from the team of doctors at the Sports Medicine Clinic when injured? In contrast, if the question of interest is "Do you agree or disagree that weather affects your performance during an athletic event? Consequently, stratified sampling would be preferred. Cluster sampling would probably be better than stratified sampling if each individual elementary school appropriately represents the entire population as in aschool district where students from throughout the district can attend any school.
Sampling Methods. Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives: Define sampling and randomization. Explain probability and non-probability sampling and describes the different types of each.
Convenience methods. Good sampling is time-consuming and expensive. Not all experimenters have the time or funds to use more accurate methods. There is a .
Sampling is the process of selecting units (e.g., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to . RESEARCH METHOD - SAMPLING 1. Sampling Techniques & Samples Types 2. Outlines Sample definition Purpose of sampling Stages in the selection of a sample Types of sampling in quantitative researches Types of sampling in qualitative researches Ethical Considerations in Data Collection 3.
Once you know your population, sampling frame, sampling method, and sample size, you can use all that information to choose your sample. Importance As you can . Another excellent source of public opinion polls on a wide variety of topics using solid sampling methodology is the Pew Research Center website at ggetlava.cf When you read one of the summary reports on the Pew site, there is a link (in the upper right corner).