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Continuous Distributions
$ a $
$ = $
$ b $
$ = $
$P(x$
≤
<
≥
>
=
≤≤
≤<
<≤
<<
$)$
$P($
≤
<
$x$
≤
<
$)$
$E(x)$
$\text{Var}(x)$
$P(z$
≤
<
≥
>
=
≤≤
≤<
<≤
<<
$)$
$P($
≤
<
$x$
≤
<
$)$
$\text{Area to the }$
left
right
$\text{ of } z \text{ is } $
$\text{Area }$
left
right
between
-z
0
$\text{and}$
z
0
$\text{is}$
$ \mu $
$ = $
$ \sigma $
$ = $
$P(x$
≤
<
≥
>
=
≤≤
≤<
<≤
<<
$)$
$P($
≤
<
$x$
≤
<
$)$
$x \text{ is in the }$
lower
upper
%
$ n $
$ = $
$ p $
$ = $
$\mu$
$\sigma$
$P(x$
=
≤
<
≥
>
)
$ \mu $
$ = $
$P(x$
≤
<
≥
>
=
≤≤
≤<
<≤
<<
$)$
$P($
≤
<
$x$
≤
<
$)$
$ df $
$ = $
Right
Left
$\text{ of } t=$
$P($
≤
<
$x$
≤
<
$)$
Upper
Lower
$\text{ tail area is }$
.20
.10
.05
.025
.01
.005
$\text{Area }$
left
right
between
-z
0
$\text{and}$
z
0
$\text{is}$
$ df $
$ = $
$\text{Upper tail area is }$
.995
.99
.975
.95
.90
.10
.05
.025
.01
.005
$ \text{Num. } df $
$ = $
$ \text{Den. } df $
$ = $
$\text{Upper tail area is }$
.10
.05
.025
.01
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Uniform Distribution
Standard Normal Distribution
Normal Distribution
Approximation of Binomial
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t-Distribution
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F-Distribution
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Example 1
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Example 2
Example 1
•
Example 2
Example 1
•
Example 2
Example 1
•
Example 2
Example 1
•
Example 2
Example 1
•
Example 2
Example 1
•
Example 2
Example 1
•
Example 2