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Praxis Core Math
Course: Praxis Core Math > Unit 1
Lesson 3: Statistics and probability- Data representations | Lesson
- Data representations | Worked example
- Center and spread | Lesson
- Center and spread | Worked example
- Random sampling | Lesson
- Random sampling | Worked example
- Scatterplots | Lesson
- Scatterplots | Worked example
- Interpreting linear models | Lesson
- Interpreting linear models | Worked example
- Correlation and Causation | Lesson
- Correlation and causation | Worked example
- Probability | Lesson
- Probability | Worked example
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Random sampling | Lesson
What are random samples?
A provides information about a without having to survey the entire group.
To make valid conclusions about a population, we need a sample that recreates the characteristics of the entire population on a smaller scale.
A good sample is representative and random.
- Representative means that the sample includes only members of the population being studied.
- Random means that every member of the population being studied has an equal chance to be selected for the sample.
What skills are tested?
- Identifying a valid sampling method
- Determining the population for which the conclusions of a sample are valid
- Using a random sample to make an estimate
What are some bad ways to sample?
Sampling method refers to how participants are selected for a sample.
Bad sampling methods include those that:
- Gather data from outside the population being studied
- Gather data that overrepresent or underrepresent a subgroup of the population (not random)
What population can we make inferences about using data from a sample?
We can make inferences about only the population from which the random sample was selected.
How can we use sample data to make an estimate?
We can use data from a random sample to estimate the number in the population having a particular attribute.
To make an estimate, we need to know the and the population size.
Your turn!
Things to remember
A is a way to gather information about a without having to survey the entire group.
- A good sample must be both and !
We can use the results of a good sample to make estimates about the population it was drawn from.
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- Estimates are valid only for the specific population the sample is drawn from!
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