What sampling technique is used when you are putting all the names of population members in a box and draw?

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. The following sampling methods are examples of probability sampling:

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What sampling technique is used when you are putting all the names of population members in a box and draw from the box the total number of the sample?
What sampling technique is used when you are putting all the names of population members in a box?
What is the sampling technique in which members of the population?
What is the method of choosing samples in which all the members of the population are given an equal chance of being 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.

Stratified Sampling is possible when it makes sense to partition the population into groups based on a factor that may influence the variable that is being measured. These groups are then called strata. An individual group is called a stratum. With stratified sampling one should:

partition the population into groups (strata)
obtain a simple random sample from each group (stratum)
collect data on each sampling unit that was randomly sampled from each group (stratum)

Stratified sampling works best when a heterogeneous population is split into fairly homogeneous groups. Under these conditions, stratification generally produces more precise estimates of the population percents than estimates that would be found from a simple random sample. Table 2.2 shows some examples of ways to obtain a stratified sample.

Table 2.2. Examples of Stratified Samples

	Example 1	Example 2	Example 3
Population	All people in the U.S.	All PSU intercollegiate athletes	All elementary students in the local school district
Groups (Strata)	4 Time Zones in the U.S. (Eastern, Central, Mountain, Pacific)	26 PSU intercollegiate teams	11 different elementary schools in the local school district
Obtain a Simple Random Sample	500 people from each of the 4 time zones	5 athletes from each of the 26 PSU teams	20 students from each of the 11 elementary schools
Sample	4 × 500 = 2000 selected people	26 × 5 = 130 selected athletes	11 × 20 = 220 selected students

Cluster Sampling is very different from Stratified Sampling. With cluster sampling, one should

divide the population into groups (clusters).
obtain a simple random sample of so many clusters from all possible clusters.
obtain data on every sampling unit in each of the randomly selected clusters.

It is important to note that, unlike with the strata in stratified sampling, the clusters should be microcosms, rather than subsections, of the population. Each cluster should be heterogeneous. Additionally, the statistical analysis used with cluster sampling is not only different but also more complicated than that used with stratified sampling.

Table 2.3. Examples of Cluster Samples

	Example 1	Example 2	Example 3
Population	All people in the U.S.	All PSU intercollegiate athletes	All elementary students in a local school district
Groups (Clusters)	4 Time Zones in the U.S. (Eastern, Central, Mountain, Pacific.)	26 PSU intercollegiate teams	11 different elementary schools in the local school district
Obtain a Simple Random Sample	2 time zones from the 4 possible time zones	8 teams from the 26 possible teams	4 elementary schools from the l1 possible elementary schools
Sample	every person in the 2 selected time zones	every athlete on the 8 selected teams	every student in the 4 selected elementary schools

Each of the three examples that are found in Tables 2.2 and 2.3 was used to illustrate how both stratified and cluster sampling could be accomplished. However, there are obviously times when one sampling method is preferred over the other. The following explanations add some clarification about when to use which method.

With Example 1: 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 many advantages over simple random sampling.
With Example 2: 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?" The answer to this question would probably not be team dependent, so cluster sampling would be fine. In contrast, if the question of interest is "Do you agree or disagree that weather affects your performance during an athletic event?" The answer to this question would probably be influenced by whether or not the sport is played outside or inside. Consequently, stratified sampling would be preferred.
With Example 3: Cluster sampling would probably be better than stratified sampling if each individual elementary school appropriately represents the entire population as in a school district where students from throughout the district can attend any school. Stratified sampling could be used if the elementary schools had very different locations and served only their local neighborhood (i.e., one elementary school is located in a rural setting while another elementary school is located in an urban setting.) Again, the questions of interest would affect which sampling method should be used.

The most common method of carrying out a poll today is using Random Digit Dialing in which a machine random dials phone numbers. Some polls go even farther and have a machine conduct the interview itself rather than just dialing the number! Such "robocall polls" can be very biased because they have extremely low response rates (most people don't like speaking to a machine) and because federal law prevents such calls to cell phones. Since the people who have landline phone service tend to be older than people who have cell phone service only, another potential source of bias is introduced. National polling organizations that use random digit dialing in conducting interviewer based polls are very careful to match the number of landline versus cell phones to the population they are trying to survey.

What sampling technique is used when you are putting all the names of population members in a box and draw from the box the total number of the sample?

Using the lottery method is one of the oldest ways and is a mechanical example of random sampling. In this method, the researcher gives each member of the population a number. Researchers draw numbers from the box randomly to choose samples.

What sampling technique is used when you are putting all the names of population members in a box?

In stratified sampling you use all the groups and some of the members in each group. Cluster sampling is the other way around. It uses some of the groups and all the members in each group.

What is the sampling technique in which members of the population?

Probability sampling means that every member of the population has a chance of being selected. It is mainly used in quantitative research. If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.

What is the method of choosing samples in which all the members of the population are given an equal chance of being selected?

Simple random sampling. In simple random sampling (SRS), each sampling unit of a population has an equal chance of being included in the sample. Consequently, each possible sample also has an equal chance of being selected. To select a simple random sample, you need to list all of the units in the survey population.