Exploring the Relationship Between Telescoping Sums and Squares

In summary, the proof in the text uses a telescoping sum to prove the formula for the partial geometric series, by multiplying both sides by 1-x and substituting x = e^t. By expanding (i+1)^3, the proof shows the relevance of this to i^2.
  • #1
nameVoid
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the proof in my text starts with what's called a telescoping sum (1+i^3)-i^3 what is the relevence of this to i^2
 
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  • #2
a) Prove the formula for the partial geometric series:

[tex]\sum_{k=0}^{n}x^{k}=\frac{1-x^{n+1}}{1-x}[/tex]


Hint: Multiply both sides by 1-x.


b) Substitute x = e^t in the formula for the partial geometric series.


c) Perform a series expansion of both sides to second order in t.
 
  • #3
nameVoid said:
the proof in my text starts with what's called a telescoping sum (1+i^3)-i^3 what is the relevence of this to i^2

Shouldn't that be (1+i)^3 - i^3?

If you expand (i+1)^3, you see that i^3 cancels and then you get a combinaton of the summaton of i^2 and i and of 1.
 

1. What is the sum of squares proof?

The sum of squares proof is a mathematical proof that shows how the sum of the squared differences between each data point and the mean of a set of data can be used to calculate the variance of the data set.

2. How does the sum of squares proof relate to statistics?

The sum of squares proof is an important tool in statistics, specifically in calculating the variance and standard deviation of a data set. It is also used in regression analysis and ANOVA (analysis of variance) to determine the significance of the relationship between variables.

3. What are the assumptions of the sum of squares proof?

The sum of squares proof assumes that the data is normally distributed and that the data points are independent of each other. It also assumes that the data is measured on an interval or ratio scale.

4. How is the sum of squares proof calculated?

The sum of squares proof is calculated by taking the sum of the squared differences between each data point and the mean of the data set. This value is then divided by the number of data points minus one, which gives the variance of the data set.

5. Why is the sum of squares proof important?

The sum of squares proof is important because it allows us to determine the spread or variability of a data set. It is also a key component in many statistical analyses, providing valuable information about the relationship between variables and the significance of results.

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