Modeling Nonlinear Data
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"Title" Tutorial Summary : 
This tutorial describes the way to model nonlinear data. We will identify exponential and power functions. Through which we can transform exponential and power functions into linear functions. And then by using properties of logarithms, we can create a model for nonlinear data.
We will also discuss the relationship between errors and residuals. Then we will also introduce studentized residual for further applications.

Tutorial Features: 
Specific Tutorial Features:
 Studentized residuals are used because the variances of the residuals differ, even though the variances of the true errors are all equal to each other.
 Leastsquares regression techinques is used to minimize residual between the data points and the curve.
Series Features:
 Concept map showing interconnections of new concepts in this tutorial and those previously introduced.
 Definition slides introduce terms as they are needed.
 Visual representation of concepts
 Animated examples—worked out step by step
 A concise summary is given at the conclusion of the tutorial.

"Title" Topic List: 
 Linear growth
 Exponential growth
 Common Ratio
 Algebraic Properties of Logarithms
 Studentized Residual

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