Z-score, CDF of normal distributions
x→Z-score→CDF ***
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The empirical rule: within 1, 2, 3 SDs of the mean.
Using z=1,2,3
"Calculate Between CDF by Z"
az=-1 bz=1 slice area/probability= ________
az=-2 bz=2 slice area/probability= ________
az=-3 bz=3 slice area/probability= ________
The empirical rule "slices":
az=0 bz=1 slice area/probability= ________
az=-1 bz=0 slice area/probability= ________
az=1 bz=2 slice area/probability= ________
az=-2 bz=-1 slice area/probability= ________
az=2 bz=3 slice area/probability= ________
Right tail from 2SD to 3SD ~1/47 of the population
az=-3 bz=-2 slice area/probability= ________
Left tail from -3SD to -2SD
Left Half of the 34.1% "slice" from mean to +1 SD:
az=0 bz=0.5 slice area/probability= ________
Right Half of the 34.1% "slice" from mean to +1 SD:
az=0.5 bz=1 slice area/probability= ________
Notice that these two halves do not have the same area.
az=-0.675 bz=0.675 slice area/probability= ________ ==IQR
The middle half of the data/population is within [-.675,.675] of the mean.
-4 is practically -∞ All the way from the left.
az=-4 bz=-3 area/probability= ________
~1/769 of the population.
az=-4 bz=-2 area/probability= ________
az=-4 bz=-1 area/probability= ________
az=-4 bz=0 area/probability= ________
az=-4 bz=1 area/probability= ________
az=-4 bz=2 area/probability= ________
az=-4 bz=3 area/probability= ________
az=-4 bz=4 area/probability= ________
Set mean=100 SD=10
"Calculate Between CDF by X"
ax=90 bx=110 slice area/probability= ________
ax=80 bx=120 slice area/probability= ________
ax=70 bx=130 slice area/probability= ________
ax=100 bx=110 slice area/probability= ________
ax=90 bx=100 slice area/probability= ________
ax=100 bx=120 slice area/probability= ________
ax=80 bx=100 slice area/probability= ________
Left Half of the 34.1% "slice" from mean to +1 SD:
ax=100 bx=105 slice area/probability= ________
Right Half of the 34.1% "slice" from mean to +1 SD:
ax=105 bx=110 slice area/probability= ________
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Clear
"Calculate CDF" is the cumulative area/probability from -∞ to a Z-score.
% of data less than this Z-score
z score=-2 "Calculate CDF" pink area/probability= ________
z score=-1 "Calculate CDF" pink area/probability= ________
z score= 0 "Calculate CDF" pink area/probability= ________
z score= 1 "Calculate CDF" pink area/probability= ________
z score= 2 "Calculate CDF" pink area/probability= ________
z score= 3 "Calculate CDF" pink area/probability= ________
Notice that these are almost the same as the above "Calculate Between CDF by Z" from -4 to this Z.
Set mean=100 SD=10
x datum → z-score → CDF(z):
x=100 → Z score=_______
Calculate CDF. Left: P(≤z) = CDF(z) = ________ Right:P(≥z)=1-CDF(z)=_______
pink area < x(Z) yellow area > x(Z)
x=90 → Z score=_______
Calculate CDF. Left: P(≤z) = CDF(z) = ________ Right:P(≥z)=1-CDF(z)=_______
x=110 → Z score=_______
Calculate CDF. Left: P(≤z) = CDF(z) = ________ Right:P(≥z)=1-CDF(z)=_______
x=80 → Z score=_______
Calculate CDF. Left: P(≤z) = CDF(z) = ________ Right:P(≥z)=1-CDF(z)=_______
x=120 → Z score=_______
Calculate CDF. Left: P(≤z) = CDF(z) = ________ Right:P(≥z)=1-CDF(z)=_______
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Clear
Going "backwards" from CDF to Z score. Given an area or probability or percentage of
the data, what is the corresponding Z score?
Left: P(≤z) = CDF(z) = .5
"InvNorm CDF (Quantile)" z score:________
Left: P(≤z) = CDF(z) = .8413
"InvNorm CDF (Quantile)" z score:________
Left: P(≤z) = CDF(z) = .9772
"InvNorm CDF (Quantile)" z score:________
Left: P(≤z) = CDF(z) = .25
InvNorm CDF (Quantile) z score:________ == Q1
Left: P(≤z) = CDF(z) = .75
InvNorm CDF (Quantile) z score:________ == Q3
Now do for a normal data set
Clear. Set mean=100 SD=10
It determines the X of a particular CDF.
Left: P(≤z) = CDF(z) = .5
"InvNorm CDF (Quantile)" z score:________ x:_______
Left: P(≤z) = CDF(z) = .8413
"InvNorm CDF (Quantile)" z score:________ x:_______
Left: P(≤z) = CDF(z) = .9772
"InvNorm CDF (Quantile)" z score:________ x:_______
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"Special areas/percentages" "Special z scores"
Symmetrically about the mean
90% of the area/data == left and right tails each 5%
Left: P(≤z) = CDF(z) = .95
"InvNorm CDF (Quantile)" z score:________ Yellow right tail is 5%
Left: P(≤z) = CDF(z) = .05
"InvNorm CDF (Quantile)" z score:________ Pink left tail is 5%
(NB. these z scores are the ± of each other)
"Calculate Between CDF by Z" using these 2 z scores.
So 90% of the area/probability/data is between [______,________]
95% of the area/data == left and right tails each 2.5%
Left: P(≤z) = CDF(z) = .975
"InvNorm CDF (Quantile)" z score:________ Yellow right tail is 2.5%
Left: P(≤z) = CDF(z) = .025
"InvNorm CDF (Quantile)" z score:________ Pink left tail is 2.5%
(NB. these z scores are the ± of each other)
"Calculate Between CDF by Z" using these 2 z scores.
So 95% of the area/probability/data is between [______,________]
99% of the area/data == left and right tails each 0.5% (half a percent, tiny)
Left: P(≤z) = CDF(z) = .995
"InvNorm CDF (Quantile)" z score:________ Yellow right tail is 0.5%
Left: P(≤z) = CDF(z) = .005
"InvNorm CDF (Quantile)" z score:________ Pink left tail is 0.5%
(NB. these z scores are the ± of each other)
"Calculate Between CDF by Z" using these 2 z scores.
So 99% of the area/probability/data is between [______,________]
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Typical kind of questions:
A population with mean μ=89.5 and SD σ=12.8
A datum x=76.2 is greater than ______% of the population.
It is less than ______% of the population.
A datum x=96.8 is greater than ______% of the population.
It is less than ______% of the population.
Between 76.2 and 96.8 is _______% of the population.
What datum value is at the 70%ile of the population:_______
i.e. is larger than 70% and less than 30%
What datum value is at the 30%ile of the population:_______
What datum value is Q1 of the population:_______
What datum value is Q3 of the population:_______
What datum value is 1.2σ above the mean:_______
What datum value is 1.2σ below the mean:_______