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Sample Surveys - AP Stats Chapter 12
Transcript of Sample Surveys - AP Stats Chapter 12
Ap Stats - Chapter 12
Or "Deep Thoughts with Darth Vader"
Samples are smaller groups from the population.
We hope that our sample REPRESENTS the population.
We must RANDOMIZE our sample to help it to REPRESENT the population.
If a sample does not represent the population well, then we say it is BIAS.
Some types of BIAS include:
Voluntary Response Bias - This can occur when the people responding to the survey "volunteer" their answers.
Undercoverage - This happens when a portion of the population is not respresented at all or not enough.
Nonresponse Bias - This occurs when potential respondents can not or will not respond.
Response Bias - This occurs when something in the survey's design influences the responses.
Why is RANDOMIZATION important?
Randomization helps to lower the chances of bias.
Randomizing protects us from ALL the influences on our population.
Randomization allows us to make inferences about our data.
Sample Size is important!
The FRACTION or PERCENT of the population in your sample is NOT important. The sample size itself is what is important.
It's true that the larger the sample size, the more accurate the results.
But just because a sample size of 100 is good for a population of 3000, it doesn't mean that a sample size of 1000 is needed for a population of 30,000.
Why not just take a census?
A census is when or "sample" is the entire population.
It's hard to survey everyone. You almost always miss some.
Tracking down the last few for a complete census can cost a lot more than your budget allows.
parameters vs statistics
Other thoughts . . .
A parameter is a numerical value that is true about a population. That's why it is sometimes called a POPULATION PARAMETER.
A statistic is a numerical value that is comes from a sample. That's why it is sometimes called a SAMPLE STATISTIC.
We hope that our sample statistics is a good representation of the population parameter.
know your symbols!
How can I collect my sample?
Simple Random Sampling (SRS)