{"id":673,"date":"2023-03-01T22:15:37","date_gmt":"2023-03-01T22:15:37","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/introstatstest\/?post_type=chapter&p=673"},"modified":"2025-08-31T10:30:55","modified_gmt":"2025-08-31T10:30:55","slug":"sampling-methods-and-bias-learn-it-3-2","status":"publish","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/sampling-methods-and-bias-learn-it-3-2\/","title":{"raw":"Sampling Methods and Bias: Learn It 2","rendered":"Sampling Methods and Bias: Learn It 2"},"content":{"raw":"

Systematic Sampling<\/h2>\r\n

In systematic sampling<\/strong>, every individual in the population is given a number, and individuals\/entities are chosen at regular intervals, with a random starting point (usually among the first several).<\/p>\r\n

The following figure illustrates a systematic sample where every 4th individual is selected, starting at the 3rd individual (starting point selected at random). The individuals selected for the sample are highlighted.\r\n[caption id=\"attachment_5722\" align=\"alignnone\" width=\"883\"]\"Appropriate Figure 1. A systematic sample selects individuals at regular intervals, starting from a randomly chosen point.[\/caption]\r\n<\/section>\r\n

Stratified Sampling<\/h2>\r\n

In stratified sampling<\/strong>, a population is divided into two or more groups (these groups are collectively called strata<\/strong>, referring to one of several groupings is known as a stratum<\/strong>) according to some criterion (i.e., geographic location, grade level, age group, income group, etc.), and a sample is selected from each stratum using simple random sampling or systematic sampling.<\/p>\r\n

In the illustration below, the population is divided into two groups (blue and green), and 4 samples were selected from each group.\r\n[caption id=\"attachment_5724\" align=\"alignnone\" width=\"881\"]\"The Figure 2. A stratified sample is created by dividing the population into groups and then selecting individuals from each group.[\/caption]\r\n<\/section>\r\n

Cluster Sampling<\/h2>\r\n

Similar to stratified sampling, for cluster sampling,<\/strong> a population is divided into two or more groups (called clusters<\/strong>) according to some criterion. Clusters are then randomly selected, and every individual in the cluster(s) is included in the sample.<\/p>\r\n

In the illustration below, the population is divided into four groups (green, purple, blue, and gray), and an entire group (blue) was chosen as the sample.
\r\n[caption id=\"attachment_1835\" align=\"alignnone\" width=\"840\"]\"The Figure 3. A cluster sample selects an entire group from a divided population.[\/caption]\r\n<\/section>\r\n

Convenience Sampling<\/h2>\r\n

A\u00a0convenience sampling<\/strong>\u00a0is a sample of individuals who are most accessible to the researcher. A convenience sample is usually not random or representative of the population. This is an example of a biased<\/strong> sampling method because it tends to produce samples that are not representative of the population. For example, you might take a sample of your friends because it is easy to collect information about them.<\/p>\r\n

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[ohm2_question hide_question_numbers=1]683[\/ohm2_question]<\/p>\r\n<\/section>","rendered":"

Systematic Sampling<\/h2>\n

In systematic sampling<\/strong>, every individual in the population is given a number, and individuals\/entities are chosen at regular intervals, with a random starting point (usually among the first several).<\/p>\n

The following figure illustrates a systematic sample where every 4th individual is selected, starting at the 3rd individual (starting point selected at random). The individuals selected for the sample are highlighted.<\/p>\n
\"Appropriate
Figure 1. A systematic sample selects individuals at regular intervals, starting from a randomly chosen point.<\/figcaption><\/figure>\n<\/section>\n

Stratified Sampling<\/h2>\n

In stratified sampling<\/strong>, a population is divided into two or more groups (these groups are collectively called strata<\/strong>, referring to one of several groupings is known as a stratum<\/strong>) according to some criterion (i.e., geographic location, grade level, age group, income group, etc.), and a sample is selected from each stratum using simple random sampling or systematic sampling.<\/p>\n

In the illustration below, the population is divided into two groups (blue and green), and 4 samples were selected from each group.<\/p>\n
\"The
Figure 2. A stratified sample is created by dividing the population into groups and then selecting individuals from each group.<\/figcaption><\/figure>\n<\/section>\n

Cluster Sampling<\/h2>\n

Similar to stratified sampling, for cluster sampling,<\/strong> a population is divided into two or more groups (called clusters<\/strong>) according to some criterion. Clusters are then randomly selected, and every individual in the cluster(s) is included in the sample.<\/p>\n

In the illustration below, the population is divided into four groups (green, purple, blue, and gray), and an entire group (blue) was chosen as the sample.<\/p>\n
\"The
Figure 3. A cluster sample selects an entire group from a divided population.<\/figcaption><\/figure>\n<\/section>\n

Convenience Sampling<\/h2>\n

A\u00a0convenience sampling<\/strong>\u00a0is a sample of individuals who are most accessible to the researcher. A convenience sample is usually not random or representative of the population. This is an example of a biased<\/strong> sampling method because it tends to produce samples that are not representative of the population. For example, you might take a sample of your friends because it is easy to collect information about them.<\/p>\n

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