Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Population
12%
20%
8%
60%
Sample
0%
0%
0%
0%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Simple Random Sampling
Using a sampling frame, each element is assigned an individual number and a random number generator decides on the elements that are included in the study. Gives every element in the target population, an equal chance of being selected. Therefore, yields samples that should be representative of the population.
Population
12%
20%
8%
60%
Sample
4%
24%
0%
72%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Systematic random sampling
Random selection is made of the first element for the sample and then subsequent elements are selected using a fixed or systematic interval until the desired sample size is reached. The target population need not be numbered or a sampling frame be compiled in case of continuous flow of the population.
Population
12%
20%
8%
60%
Sample
8%
28%
4%
60%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Stratified Random Sampling
Target population is first separated into mutually exclusive, homogeneous segments (strata), and then a simple random sample is selected from each segment (stratum). The proportions in the sample match the proportions in the population.
Population
12%
20%
8%
60%
Sample
12%
20%
8%
60%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Cluster Sampling
Probability sampling procedure in which elements of the population are randomly selected in naturally occurring groupings (clusters). The clusters are randomized and all elements within the cluster form part of the sample. Can be based on location: states, counties, blocks, buildings Or organisation based: schools, grade levels or classes, clinic, practitioner...
Population
12%
20%
8%
60%
Sample
14%
23%
3%
60%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Multistage Sampling
Random sampling but in multiple stages that may use a mix of cluster, stratification and simple random sample. Usually done when the population is very large and there are obvious subgroups that can help organize the total population.
Example: A researcher wants to investigate the prevalence of dental trauma within the previous year for Queensland children under 10 years of age. 1st stage: Stratification by location (metropolitan, regional, remote) 2nd stage: Cluster random selection by local geographical area code (LGA) 3rd stage: Cluster random selection by school within LGA 4th stage: Simple random selection of children from each school
Probability sampling
Chrsitopher Sexton
Created on August 1, 2021
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Transcript
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Population
12%
20%
8%
60%
Sample
0%
0%
0%
0%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Simple Random Sampling
Using a sampling frame, each element is assigned an individual number and a random number generator decides on the elements that are included in the study. Gives every element in the target population, an equal chance of being selected. Therefore, yields samples that should be representative of the population.
Population
12%
20%
8%
60%
Sample
4%
24%
0%
72%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Systematic random sampling
Random selection is made of the first element for the sample and then subsequent elements are selected using a fixed or systematic interval until the desired sample size is reached. The target population need not be numbered or a sampling frame be compiled in case of continuous flow of the population.
Population
12%
20%
8%
60%
Sample
8%
28%
4%
60%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Stratified Random Sampling
Target population is first separated into mutually exclusive, homogeneous segments (strata), and then a simple random sample is selected from each segment (stratum). The proportions in the sample match the proportions in the population.
Population
12%
20%
8%
60%
Sample
12%
20%
8%
60%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Cluster Sampling
Probability sampling procedure in which elements of the population are randomly selected in naturally occurring groupings (clusters). The clusters are randomized and all elements within the cluster form part of the sample. Can be based on location: states, counties, blocks, buildings Or organisation based: schools, grade levels or classes, clinic, practitioner...
Population
12%
20%
8%
60%
Sample
14%
23%
3%
60%
Probability sampling
Any method that produces samples that have been randomly selected. In order for your samples to be randomly selected, you need to have mechanisms in place that will ensure that the participants have the same chance of being selected.
Multistage Sampling
Random sampling but in multiple stages that may use a mix of cluster, stratification and simple random sample. Usually done when the population is very large and there are obvious subgroups that can help organize the total population.
Example: A researcher wants to investigate the prevalence of dental trauma within the previous year for Queensland children under 10 years of age. 1st stage: Stratification by location (metropolitan, regional, remote) 2nd stage: Cluster random selection by local geographical area code (LGA) 3rd stage: Cluster random selection by school within LGA 4th stage: Simple random selection of children from each school