Com 300
4.20.10
Notes:
Probability: Playing the odds
Probability Distributions – representations of the theoretical patterns of sample data
(should look like standard normal curve)

They should be predictable
o
Example: Tossing a coin and getting heads five times in a row.
.5 x .5 x .5 x .5 x .5 = Odds are .03125 or 3%
Inferential Statistics

To know how likely it is that their sample results may have occurred by
chance alone
o
Sampling statistics
When you do non random sampling you cannot do this
Example: T test

They provide statistical tests of data significance
o
For the first time be able to take our variables and see if they
react/relate to each other
The error should be small
o
Show the potential error rate of a statistical finding and significance of
hypotheses
You could find correlations or interesting connections after the
RQ has been formed and the tests/research made
Example: correlation
Inferential: Sampling Statistics

Sampling Error – the degree to which a sample differs from population
characteristics on some measure. (only 5% allowed)

Confidence Intervals – the probability that sample statistics “capture”
population parameters, within certain margins for error

(95% or z = 1.96)
Tests for Comparing Two Means
The t – Test

Tells us if our sample mean is significantly different from the population’s
mean
o
Like ensuring you have equal republicans and democrats in a study on
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 Spring '08
 finnerty
 Statistics, Statistical hypothesis testing, Statistical significance, inferential statistic, straight diagonal line

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