Regression Lines - In Layman's Terms
To
understand linear regression, it's necessary to
understand the use of regression lines. A regression
line is used in statistical analysis to define the
difference between two variables. You can clearly
imagine a regression line being used in engineering
estimation of varying points. In the case of regression
lines, one variable will be independent and the other
dependent.
Mechanical designers often plot these on a grid where
the dependent variable will be drawn according to the
equation where Y is the dependent and X the independent
variable. This is the purpose upon which the drawing is
based. Engineers may use the standard linear regression
equation to arrive at the correct configurations.
For example, certain lines on a plotted grid may
represent a steel beam that must be attached to a load
bearing beam. The load bearing beam represents an
independent variable. The attached beam is wholly
dependent on the load bearing beam for support. From
this configuration, it's then possible to determine the
weight load the finished structure will bear. The line
of regression in this example is the location of the
load bearing beam.
Linear
Regression
Using the same example of steel
beams, imagine that the mechanical designers are
required to provide proof that the relationship between
the attached beam and load bearing beam can bear a
specific weight load of one thousand tons on a daily
basis. The design plot would need to also include this
aspect by inserting averages of tonnage most likely to
be borne by the structure.
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Linear
Regression in Statistics
In statistical engineering, linear
regression expresses the major factors in the data used.
As an example, air pressure through industrial ducts are
dependent on the power of the air source, usually a fan
or blower. It may also depend on the rate of the air
velocity and whether it is induced or drafted through
the duct system. A statistical engineer is charged with
the duty of using the independent fan or blower to
calculate the force of the air pressure in pounds per
square inch of duct. This is accomplished through the
use of linear regression on an expressed equation drawn
onto a grid. This is often referred to as linear system
analysis. In this example, a model is created by linear
mapping between system inputs and system outputs. A
system is set or an arrangement of instrumentation or
other devices fully related or connected form a unit as
a whole.
Linear
Regression and Its Uses
The factors of greatest influence on
an economy are spending, tax levels, interest rates and
the overall monetary policies. Gross national product,
unemployment rate, rate of inflation and consumer price
index are economic outputs to arrive at the main
dynamic. Statistically when data is collected on all of
these factors, the end result is the condition of the
economy. Linear regression is most often used by those
involved in various polls and census bureaus that
estimate the variables in a country's population. Copyright
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