Stats Unit 1 Lesson 3 – Flashcards
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Random Sampling Error
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The error that occurs when we estimate a population characteristic by looking at only one portion of the population rather than the entire population.
(In other words, random sampling error occurs whenever we take a sample to determine characteristics of a population)
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What is Random Sampling Error (numerically)?
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The difference between the sample proportion and the 'true' value that would result if a census of the whole population were taken under the same conditions (the population parameter).
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Characteristics of Random Sampling Error
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- Generally decreases as the sample size increases (but not proportionally)
- Depends on the variability of the characteristic of interest in the population
- Can be accounted for and reduced by an appropriate sampling plan
- Can be measured and controlled in probability sample surveys (surveys of samples of individuals selected by chance).
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Maximum size of Random Sampling error
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Can be calculated and is called the margin of error
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Short Cut formula for the margin of error for a 95% confidence interval estimate is
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1/(sq. root(n))
where n = sample size
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95% Confidence interval estimate is calculated by
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subtracting the margin of error from and adding the margin of error to the sample proportion
eg - 44% +- 6% = 38% to 50%
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Conditions that must be met to use short cut formula to find the margin of error for 95% confidence interval estimate
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- Short cut formula only works on random samples (can't use on convenience sample or if have used a voluntary response sample)
- Random sample must represent a small portion of the population (sample size must be no more than 1% of the population size)
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What do we mean by 95% confident?
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95% of all samples selected in this way (random samples) would produce an interval estimate that would contain the population parameter. Only about 5% of all samples selected in this way would produce interval estimates that do not contain the population parameter.
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How to control bias in a sample
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Take a probability sample instead of a convenience or voluntary response sample. Probability samples are sample designs that use chance to select the subjects for the sample
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How to control variability in a sample
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Take a larger sample.
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A good sampling method has both
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Small bias and small variability
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Parameter
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Fixed, unknown number that describes the population
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Statistic
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Known value calculated from a sample. Can change from sample to sample
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What is the difference between a random sample and a simple random sample?
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In a random sample, each member of the entire population has an equal chance of being selected.
In a Simple Random Sample, a group of size n is selected and every possible group has the same chance of being selected.