Any technique or trick for finding the coefficient

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In summary, the conversation is discussing techniques for finding the coefficient of a specific term in a polynomial expression. One suggestion is to use generating functions to rewrite the expression and then use a formula to calculate the coefficient. Another approach is to think about the expansion of the expression and use combinatorics to determine the different ways of selecting terms that add up to the desired exponent.
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any technique or "trick" for finding the coefficient

Here is the polynomial expression

(x+x^2+x^3+x^4+x^5+x^6)^5

Each x term is raised to ascending powers of 1.

The entire sum in the brackets is raised to the 5th power.

Does anyone have any "special trick" for finding the coefficient of the term which contains x^19?
 
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what about generating functions? there's another way to rewrite the finite geometric series inside the brackets, and that formula raised to the 5th power has another formula, and you can plug in the appropriate numbers to get the coefficient for x^19
 
  • #3


Think about how would you write out the expansion normally? You would write out the 5 factors in 5 separate brackets (..)(..)(..)(..)(..), and pick a term from each bracket to form a term on the RHS. How many ways can you pick those terms differently to get the exponents adding to 19? It's now a combinatorics problem.
 

1. How do I find the coefficient using regression analysis?

Regression analysis is a statistical technique that can be used to find the coefficient of a relationship between two variables. It involves fitting a line to a scatter plot of the data and calculating the slope of that line. This slope represents the coefficient of the relationship.

2. Can I use the coefficient from a linear regression to make predictions?

Yes, the coefficient from a linear regression can be used to make predictions about the relationship between the two variables. The coefficient represents the change in the dependent variable for every one unit change in the independent variable.

3. Is there a specific formula for calculating the coefficient?

Yes, the formula for calculating the coefficient in a linear regression is: coefficient = (nΣxy - ΣxΣy) / (nΣx^2 - (Σx)^2), where n is the number of data points, Σxy is the sum of the products of the two variables, Σx is the sum of the independent variable, and Σy is the sum of the dependent variable.

4. What is the significance of the coefficient in regression analysis?

The coefficient in regression analysis is significant because it represents the strength and direction of the relationship between the two variables. A coefficient close to 1 or -1 indicates a strong relationship, while a coefficient close to 0 indicates a weak or non-existent relationship.

5. Can I use different techniques to find the coefficient besides regression analysis?

Yes, there are other techniques that can be used to find the coefficient, such as correlation analysis, ANOVA, and chi-square tests. The appropriate technique will depend on the type of data and the research question being addressed.

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