Lesson 1: 3.1 Sampling and Surveys
Duration of Days: 4
Lesson Objective
• Identify the population and sample in a statistical study.
• Identify voluntary response sampling and convenience sampling and explain how these sampling methods can lead to bias.
• Describe how to select a simple random sample using slips of paper, technology, or a table of random digits.
• Describe how to select a sample using stratified random sampling, cluster sampling, and systematic random sampling, and explain whether a particular sampling method is appropriate in a given situation.
• Explain how undercoverage, nonresponse, wording of questions, and other aspects of a sample survey can lead to bias.
• How do I identify the population and sample in a statistical study?
• How do I identify voluntary response sampling and convenience sampling and explain how these sampling methods can lead to bias?
• How do I describe how to select a simple random sample using slips of paper, technology, or a table of random digits?
• How do I describe how to select a sample using stratified random sampling, cluster sampling, and systematic random sampling, and explain whether a particular sampling method is appropriate in a given situation?
• How do I explain how undercoverage, nonresponse, wording of questions, and other aspects of a sample survey can lead to bias?
- population
- census
- sample
- sample survey
- convenience sampling
- bias
- voluntary response sampling
- random sampling
- simple random sample (SRS)
- sampling with/without replacement
- strata, stratified random sampling
- clusters, cluster sampling
- systematic random sampling
- undercoverage
- nonresponse
- response bias
HSS-IC.A.1: Understand statistics as a process for making inferences about population parameters based on a random sample from that population.
HSS-IC.B.3: Recognize the purposes of and differences among sample surveys, experiments, and observational studies.
HSS-IC.B.4: Explain how randomization in experiments can be used to control for lurking variables.
HSS-IC.B.5: Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through simulation models.
HSS-IC.B.6: Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between sample means are statistically significant.
These concepts are essential for ensuring the validity and reliability of statistical studies. By using appropriate sampling methods and minimizing bias, researchers can draw accurate conclusions about the population of interest.
Use of dynamic problem sets through digital learning platforms with customized feedback.
Mastery-based assessment