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Beginner Statistics
!
Population vs Sample
The population includes all objects of interest whereas the sample is only a portion of the
population
...
Parameters
are usually denoted using Greek letters (mu, sigma) while statistics are usually denoted using
Roman letters (x, s)
...
They are usually large, and it is
often impossible to get data for every object we're studying
...
We compute statistics, and use them to estimate parameters
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There are a finite or countable number of
choices available with discrete data
...
63 people in the room
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Length, weight, and time are all
examples of continous variables
...
This implies a boundary depending on the number of decimal places
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5 <= x < 64
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Likewise, if there are two decimal places, then 64
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025 <= x < 63
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Boundaries always have one more decimal place than the data
and end in a 5
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These go from
lowest level to highest level
...
Each
additional level adds something the previous level didn't have
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Only names are meaningful here
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•
Interval adds meaningful differences
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Ratio adds a zero so that ratios are meaningful
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•
Random sampling is analogous to putting everyone's name into a hat and drawing out
several names
...
While
this is the preferred way of sampling, it is often difficult to do
...
Computer generated lists are often
used with random sampling
...
•
Systematic sampling is easier to do than random sampling
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That is, every kth element is taken
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When done numbering, all
people numbered 4 would be used
...
In
convenience sampling, readily available data is used
...
•
•
Cluster sampling is accomplished by dividing the population into groups -- usually
geographically
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The clusters are randomly
selected, and each element in the selected clusters are used
...
However, this
time it is by some characteristic, not geographically
...
A sample is taken from each of these strata using
either random, systematic, or convenience sampling