Home / Worksheets / Grade 12 / Math / Grade 12 Math: Random Sampling

Grade 12 Math: Random Sampling

This worksheet covers key concepts in random sampling, including definitions, types, and applications, suitable for Grade 12 Probability and Statistics.

Grade 12 Math Probability and StatisticsRandom Sampling
Use This Worksheet

Includes

Multiple ChoiceTrue / FalseFill in the BlanksShort AnswerMatching

Topics

HSS-IC.A.1HSS-IC.B.4random samplingstatisticsprobabilitygrade 12math
7 sections · Free to use · Printable
← More Math worksheets for Grade 12

Random Sampling Worksheet

Name:

Date:

Score:

Read each question carefully and provide your answer in the space provided. Show all your work for short answer questions.

1. Which of the following is the primary goal of random sampling?

a

To ensure every member of the population is included.

b

To obtain a sample that is representative of the population.

c

To select participants based on convenience.

d

To introduce bias into the study.

2. In a simple random sample, what is the probability of any given unit being selected?

a

It varies depending on the unit.

b

It is equal for all units.

c

It is higher for units with specific characteristics.

d

It is impossible to determine.

1. Stratified random sampling involves dividing the population into homogeneous subgroups and then taking a simple random sample from each subgroup.

T

True

F

False

2. Convenience sampling is a type of random sampling method.

T

True

F

False

1. A   is a subset of individuals selected from a larger population.

2.   sampling ensures that every member of the population has an equal chance of being selected.

3. When a population is divided into clusters and a random sample of these clusters is chosen, it is called   sampling.

1. Explain the difference between a population and a sample in the context of statistics.

2. Describe two advantages of using random sampling methods in research.

Match each sampling method with its description.

1. Simple Random Sampling

 

a. Dividing population into strata, then random sample from each.

2. Stratified Random Sampling

 

b. Every member has an equal chance of selection.

3. Cluster Sampling

 

c. Randomly selecting groups (clusters) from the population.