Sampling Methods in Statistics

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

• Stratified
• Systematic
• Simple
• Cluster

Mrs. Trahan samples her class by selecting every third person on her class list.  Which type of sampling method is this?

• Simple
• Systematic
• Stratified
• Cluster

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

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

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

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

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

Farmer Joe separates his farm into 10 regions.  He then randomly selected 5 trees from each region to estimate the number of apples produced on his apple tree farm.  This is _____________ sampling.  

• Cluster
• Systematic
• Stratified
• Simple

In order to use samples to estimate something from the population, the sample should be _________________ the population.

• exactly the same as
• nothing like
• representative of
• larger than

When one examines the entire population instead of a subgroup of the population, this is called a ____________.

• Sampling
• Census
• Bias