# Suppose we select every fifth invoice in a file. what type of sampling is this?

Suppose we select every fifth invoice in a file cabinet arranged
accrding to the invoice data. What type of sampling is this? A.) Simple random sampling B.) Cluster sampling C.) Stratified random sampling D.) Systematic random sampling E.) Normal distribution sampling

General guidance

Concepts and reason
Sampling:
Sampling is the technique that is used to estimate the population. A sample is selected from the population and this forms the representative of the population. Different sampling methods are used for drawing the samples.
Simple random sampling:
When all the units in the population are drawn randomly with equal probability of being selected into the sample is called as simple random sampling.
Stratified sampling:
When the units in the population are divided into subgroups and then the sample is drawn from each group then it is called as stratified sampling. The subgroups are called as strata.
Systematic sample:
In a systematic sample, starting with a unit selecting at random, every unit in the sample is selected from the population.
Cluster Random Sampling:
In cluster random sampling, the total population is divided into groups and some groups are selected by using simple random sample called as clusters. All the elements in each cluster are included in the sample.

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Fundamentals

Procedure for simple random sampling:
1.Select the population from which the sample has to be drawn.
2.Select the required sample size.
3.Assign the numbers for each unit of the population.
4.Use the random number tables to select units from the population.
5.The simple random sample is obtained.
Procedure for stratified sampling:
1.Select the population from which the sample has to be drawn.
2.Divide the population into homogeneous subgroups based on characteristics of the groups. These subgroups are called as strata.
3.Each unit of the population must be assigned to only one stratum (Subgroup).
4.Now within each stratum select the units using the procedure of the simple random sampling.
5.Combine all the sampled units of the different strata to form the stratified sample.
Procedure for systematic sampling:
1.Select the population (N) from which the sample has to be drawn.
2.Divide these N units into n groups of k units
3.Calculate the sampling fraction, .
4.Randomly select the first unit in the sample.
5.Select every unit in the sample at regular intervals.
Procedure for cluster sampling:
1.Select the population from which the sample has to be drawn.
2.Divide the population into groups. These groups are called as clusters.
3.Select a sample of groups using simple random sampling.
4.Include all the units in each of the group into the sample.

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Step-by-step

Step 1 of 2

The incorrect options are explained below:
From the information, every fifth invoice in a file cabinet arranged according to the invoice data is selected.
Selecting every fifth invoice is not simple random sampling as invoices are not just selected randomly. Also, it is not stratified sample because invoices are not divided based on the certain characteristics. It is not cluster sample as invoices are not divided into cluster. Also, there is no normal distribution sampling method.
This indicates that the options ‘Simple random sampling, cluster sampling, stratified sampling, normal distribution sampling’ is incorrect.

The sampling of every fifth invoice does not resemble the sampling methods Simple random sampling, cluster sampling, stratified sampling, normal distribution sampling’.

Use the concepts of ‘systematic sampling’ to determine the correct option.

Step 2 of 2

The correct option is explained below:
From the information, every fifth invoice in a file cabinet arranged according to the invoice data is selected.
In systematic sampling a starting point is selected and then every kth unit is selected. This indicates that selecting every fifth invoice from a file cabinet arranged is a systematic sampling.

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The sampling method is systematic sampling.

In a systematic sample, starting with a unit selecting at random, every unit in the sample is selected from the population.