1-3 Data Collection and Sampling Techniques

1-3 Data Collection and Sampling Techniques

You will be able to identify the four basic sampling techniques.

Four basic methods of sampling

• Random:  selected by using chance methods or random numbers. 

• Systematic: numbering each subject of the population and then selecting every kth subject. Chose a random 1st subject.

• Stratified: divide the population into groups (called strata) according to some characteristic that is important to the study, then sample from each group.

• Cluster Sampling: the population is divided into groups called clusters, then some of these clusters are randomly selected, and uses all members of the selected clusters as the subjects of the samples.

Simple Random Sampling Example

You want to select a simple random sample of 100 employees of Company X. You assign a number to every employee in the company database from 1 to 1000, and use a random number generator to select 100 numbers.

Systematic Sampling

All employees of the company are listed in alphabetical order. From the first 10 numbers, you randomly select a starting point: number 6. From number 6 onwards, every 10th person on the list is selected (6, 16, 26, 36, and so on), and you end up with a sample of 100 people.

Stratified Sampling

The company has 800 female employees and 200 male employees. You want to ensure that the sample reflects the gender balance of the company, so you sort the population into two strata based on gender. Then you use random sampling on each group, selecting 80 women and 20 men, which gives you a representative sample of 100 people.

Cluster Sampling

The company has offices in 10 cities across the country (all with roughly the same number of employees in similar roles). You don’t have the capacity to travel to every office to collect your data, so you use random sampling to select 3 offices – these are your clusters.

Multiple Choice

Mrs. Trahan samples her class by selecting 5 girls and 7 boys. This type of sampling is called?

• Stratified

• Systematic

• Simple

• Cluster

Multiple Choice

Farmer Joe separates his apple tree farm into 10 regions.  He counts the number of apples produced in just one of the regions and uses that estimate to predict the number of apples produced on the whole farm.  This is _______ sampling.

• Simple
• Cluster
• Stratified
• Systematic

Multiple Choice

Mrs. Trahan samples her class by picking 10 numbers from her hat and each number is assigned to a student. This is ______________ random sampling.

• Systematic
• Simple
• Stratified
• Cluster

Multiple Choice

Mrs. Trahan samples her class by selecting all students sitting at group 1 and group 5 in her classroom.  This sampling technique is called?

• Simple
• Stratified
• Systematic
• Cluster

Multiple Choice

Farmer Joe randomly picks 100 trees using a random number generator to estimate the number of apples produced by his apple trees. This is ______________ sampling.

• Simple

• Stratified

• Cluster

• Systematic

Multiple Choice

Mrs. Trahan samples her class by selecting 5 girls and 7 boys. This type of sampling is called?

• Stratified

• Systematic

• Simple

• Cluster

Multiple Choice

Farmer Joe's apple tree farm is set up in 100 rows. He counts the number of apples produced on every 10th row to estimate the number apples produced on the whole farm. This is _____________ sampling.

• Simple

• Stratified

• Cluster

• Systematic