Effortlessly Linearize y(x)= a(1-e-bx) with Expert Help

In summary: So the linearized function is y= abe^{-7.5b}(x- 7.5)+ a(1- e^{-7.5b}).In summary, the conversation discusses the process of linearizing a function and determining the parameters Rmax and k using a mathematical model. This involves approximating the function by a linear function within a limited range, and the best linear approximation can be found by taking the derivative of the function. The linearized function is y= abe^{-7.5b}(x- 7.5)+ a(1- e^{-7.5b}).
  • #1
cicleriano
2
0
Hello! how I linearize this function?

y(x)= a(1-e-bx)

a and b are constants
 
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  • #2
Unfortunately, it seems you do not understand the problem completely, as it only make sense if you offer some points at which to approximate the function. For starters...
 
  • #3
sorry!
In the flotation laboratory was determined following table of values:

time(min) - %Rec
0 - 0
1 - 45
3 - 72
5 - 80
9 - 88
12 - 91.8
15 - 92​

A mathematical model representing these results is R(t) = Rmax(1-e^-kt). Linearize the function and determine the parameters Rmax and k.
 
  • #4
To "linearize" a fuction means to approxiate it by a linear function and that can only be done accurately in a limited range. One of the things we should learn in basic Calculus is that the tangent line to a graph gives the best linear approximation to the function in a neighborhood of the given point.

The difficulty is that you can't have a linear function that accurately approximates a function for all x and here you are not saying where you want it approximated. In the list you give, x varies from 0 to 15. It would be easiest to linearize at x= 0 but I would be inclined to use the midpoint x= 7.5.

The derivative of [itex]y=a(1- e^{-bx})[/itex] is [itex]y'= abe^{-bx}[/itex] and at x= 0 that is [itex]ab[/itex]. So your linear approximation, around x= 0, is the line through (0, 0) with slope ab.

But the derivative at x= 7.5 is [itex]abe^{-7.5b}[/itex] so the linearization would be the line through [itex](7.5, a(1- e^{-7.5b}))[/itex] with slope [itex]abe^{-7.5b}[/itex].
 

What is linear regression?

Linear regression is a statistical method used to model the relationship between one or more independent variables and a dependent variable. It is a commonly used technique in data analysis to identify and predict trends and patterns in data.

How do I perform a linear regression analysis?

To perform a linear regression analysis, you will need a dataset with at least two variables, a dependent variable and one or more independent variables. You can use software such as Excel, R, or Python to perform the analysis and generate a regression line that best fits the data.

What is the purpose of a linear regression analysis?

The purpose of a linear regression analysis is to identify and quantify the relationship between the dependent variable and one or more independent variables. It can also be used to make predictions about future data based on the observed trends and patterns in the data.

What is the difference between simple and multiple linear regression?

Simple linear regression involves only one independent variable, while multiple linear regression involves two or more independent variables. Multiple regression allows for a more complex analysis and can provide more accurate predictions, but it also requires more data and assumptions to be met.

How do I interpret the results of a linear regression analysis?

The most important result of a linear regression analysis is the regression line, which shows the relationship between the dependent and independent variables. The slope of the line represents the change in the dependent variable for every one unit change in the independent variable. The intercept represents the value of the dependent variable when the independent variable is zero. Other important results include the coefficient of determination (R-squared) and the p-value, which indicate the strength and significance of the relationship between the variables.

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