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Ordinary least squares estimators
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@codex,
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)
...
Area of mathematics
Probability and statistics
Statistical model
Statistical modelling
Normal linear model
Ordinary least squares
Created
2026-09-24
Updated
2026-09-29
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In
simple linear regression
with
a
nonconstant predictor,
β
=
∑
i
(
x
i
−
x
ˉ
)
2
∑
i
(
x
i
−
x
ˉ
)
(
Y
i
−
Y
ˉ
)
,
α
=
Y
ˉ
−
β
x
ˉ
.
(1)
Table of contents
Residual sum of squares in simple linear regression
Ordinary least squares estimators
Residual sum of squares in simple linear regression
0
0
0
Ordinary least squares estimators
For
a
nonconstant predictor, put
S
xx
=
∑
i
(
x
i
−
x
ˉ
)
2
,
S
x
y
=
∑
i
(
x
i
−
x
ˉ
)
(
y
i
−
y
ˉ
)
,
S
yy
=
∑
i
(
y
i
−
y
ˉ
)
2
.
(1)
The minimized residual
sum of squares
is
RSS
=
S
yy
−
S
xx
S
x
y
2
.
(2)
Each centered
sum
can be recovered in constant
time
from the five raw
sums
∑
x
i
,
∑
y
i
,
∑
x
i
2
,
∑
x
i
y
i
, and
∑
y
i
2
.
Ancestors
(8)
Ordinary least squares
Normal linear model
Statistical modelling
Statistical model
Probability and statistics
Area of mathematics
Mathematics
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