Why Do Taylor Series Solutions Sometimes Exclude the Constant C?

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In summary, the conversation discusses solving problems involving finding the value of "e" and cosine with a specified error. The solutions involve finding Taylor series and choosing a point on an interval for the remainder term. The conversation also mentions using a Maclaurin series and solving for the number of terms required to meet a specific precision. One problem involves finding the value of sqrt(5) using a binomial series and solving a trial-and-error method to determine the number of terms needed.
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transgalactic
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i added a file with the questions
and the solutions of the book

http://img178.imageshack.us/my.php?image=img7565zj6.jpg

question 1 is:
calculate "e" with an error less than 10^-9??
i started the solving of this problem
by finding the expretion of Rn for e^X
NEXT
we need to chhose a point C which is located between X and A
A<c<X
i know that X equals to 1
but why in the solution they tell that A=0?

question 2 is:

find cos 9 with an error less than 10^-5 (9 is degrees not radians)
here after findinf the expretion of Rn
where did i use to put "c"
because they solve this problem without c
i don't know why??


question 3:
i dint understand the way they solved it
because they didnt use any tailor series here
where is the function that i need to build a tailor series from??
 
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  • #2
transgalactic said:
question 1 is:
calculate "e" with an error less than 10^-9??
i started the solving of this problem
by finding the expretion of Rn for e^X
NEXT
we need to chhose a point C which is located between X and A
A<c<X
i know that X equals to 1
but why in the solution they tell that A=0?

a is zero because you are using a Maclaurin series for e^x, that is, a Taylor series for the function expanded about x = a = 0.

It seems from your note that the problem is asking you to find the number of terms in the Taylor polynomial that would be required to find e^x to a precision of 10^-9 on the interval [0,1]. This will let you find e^1 = e to the desired precision.

You will not need to choose c: it is just a point on the interval for which we are guaranteeing that the size of the remainder for the Taylor polynomial will be less than the selected precision. The numerator in the remainder term needs to be the maximum value that the nth derivative of e^x has on [0,1], which will in fact be e^1. But since we're supposed to be computing a value for e, we have to pretend that we don't already know it, so we set that maximum value to 3, which we're pretty sure is bigger than e...

That leaves you to solve 3/(n+1)! < 10^-9 , which doesn't work algebraically and has to be done by one or another sophisticated "trial-and-error" method.

question 2 is:

find cos 9º with an error less than 10^-5
here after findinf the expretion of Rn
where did i use to put "c"
because they solve this problem without c
i don't know why??

Once again, they are using a Maclaurin series for cos(x), so a=0. The Taylor remainder term needs a largest value for the nth derivative on some interval around x = 0. But since all the derivatives of cos(x) are +/-sin(x) or +/-cos(x), the largest value is guaranteed to be one. So in practice, we don't worry about a value for c: we just put in a "1" in the remainder term and solve for the number of terms as you show in your notes.


question 3:
i dint understand the way they solved it
because they didnt use any tailor series here
where is the function that i need to build a tailor series from??

Actually, they did work out a Taylor series. The problem is apparently to find sqrt(5) using a Maclaurin series based on (1+x)^p (for some reason, they used something like a cursive-L for the exponent, which I'm not going to attempt to reproduce).

So they said: let's factor 5^(1/2) as (4+1)^(1/2) =
2 · [ (1 + {1/4})]^(1/2) and work out the general Taylor series for a binomial (1+x) raised to any real power (which they do on the next line).

They then set up the remainder term for this series, with the exponent now set to p = (1/2) and the interval going out to
x = 1/4 ; the nth derivative isn't hard to find, but solving the inequality to find the number of terms required to meet a precision of 5·10^-3
( which they write as (10^-4)/2 ) isn't going to get done algebraically, so they must have done a "trial-and-error" solution. They find that terms out to n=4 are needed and proceed to make the calculation to obtain an estimate for sqrt(5).
 
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FAQ: Why Do Taylor Series Solutions Sometimes Exclude the Constant C?

What is the "3 questions in tailor series"?

The "3 questions in tailor series" is a series of three questions used in the field of statistics to assess the fit of a model to a given dataset. These questions are commonly used to evaluate the effectiveness of a model in predicting or explaining a phenomenon.

What are the three questions in the tailor series?

The three questions in the tailor series are:

  1. How well does the model fit the data?
  2. Are the model's assumptions fulfilled?
  3. How well does the model generalize to unseen data?

Why are these questions important in statistics?

These questions are important in statistics because they help to evaluate the effectiveness and accuracy of a model. By asking these questions, scientists can determine if the model is a good fit for the data and if it can be used to make predictions or draw conclusions about the phenomenon being studied.

How are the three questions in the tailor series answered?

The first question is typically answered by evaluating the model's goodness of fit statistics, such as the coefficient of determination (R^2) or the root mean squared error (RMSE). The second question is answered by checking if the model's assumptions, such as normality and homoscedasticity, are met. The third question is answered by testing the model on new data or using cross-validation techniques.

Can the tailor series be applied to any type of model?

Yes, the tailor series can be applied to any type of model, from simple linear regression to more complex machine learning algorithms. It is a general framework for evaluating the performance and assumptions of models in statistics.

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