Linearization

Linearization is

• a mathematical trick to allow the use of basic algebra to find the equation for a non-linear data set

• a process of fixing bad data so it looks like a line

• a process of changing data so it looks like a line

• a process for replacing data with more accurate results that form a perfect line of best fit.

When you use linearization the equation you find from the linearized graph works for the

• original data graph

• the linear test plot

• neither graph

• both graphs

Linearization _____________ change the relationship between the tested variables to a linear relationship.

• does

• does not

If the data graph shows a hyperbola you should

• inverse the x-varibale

• square the x-variable

• square the y-variable

• inverse the y-variable

If the data graph shows a top opening parabola you should

• inverse the x-variable

• inverse the y-variable

• square the x-variable

• square the y-variable

If the data graph shows a side opening parabola then you should

• inverse the x-variable

• inverse the y-variable

• square the x-variable

• square the y-variable

When the relationship between two variables is inverse this means that as the one variable gets bigger the other

• also gets bigger.

• stays the same.

• gets smaller.

• gets bigger much faster.

When linearizing in logger pro you should

• do the calculations by hand and type them into a new manual column

• use a calculated column and make logger pro do the calculations

When the original data graph come out as a diagonal line then you should

• square the x-variable to linearize.

• square the y-variable to linearize.

• inverse the x-variable to linearize.

• nothing it is already linear.

When the original data set comes out as a horizontal line it means

• the dependent variable is not affected by the independent variable

• the experiment was done incorrectly

• the dependent variable is linearly dependent on the independent variable.