MHB Finding the Set of Ordered Triples of a Ternary Relation on A

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The discussion focuses on finding ordered triples (x, y, z) for the ternary relation R defined by the equation x^2 + 4y = z, with constraints that x, y, and z must be between 1 and 20. An exhaustive search reveals valid triples including (1,1,5), (1,2,9), (1,3,13), (1,4,17), (2,1,8), (2,2,12), (2,3,16), (2,4,20), (3,1,13), (3,2,17), and (4,1,20). Values of x and y beyond certain limits yield z values exceeding 20, thus are excluded. The complete set of valid ordered triples is provided, confirming all calculations adhere to the defined constraints. The findings illustrate the relationship between the variables within the specified range.
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Given that A = {1, 2, 3 ……..20} and R is a ternary relation on A defined by equation
x2 + 4y = z .Find the set of ordered triples of R.
 
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trevor said:
Given that A = {1, 2, 3 ……..20} and R is a ternary relation on A defined by equation
x2 + 4y = z .Find the set of ordered triples of R.

spitballin' it ... hope I didn't miss any

(1,1,5), (1,2,9), (1,3,13), (1,4,17)

(2,1,8), (2,2,12), (2,3,16), (2,4,20)

(3,1,13), (3,2,17)

(4,1,20)

tenor.gif
 
Too late... Posting anyway.

We need to find all triples $(x,y,z)$ such that $x^2+4y=z$ and $1\le x,y,z\le 20$. Let's do an exhaustive search.

$x=1,y=1\implies z=5$
$x=1,y=2\implies z=9$
$x=1,y=3\implies z=13$
$x=1,y=4\implies z=17$
$x=1,y=5\implies z=21$; this does not satisfy $z\le 20$.
$x=2,y=1\implies z=8$
$x=2,y=2\implies z=12$
$x=2,y=3\implies z=16$
$x=2,y=4\implies z=20$
$x=3,y=1\implies z=13$
$x=3,y=2\implies z=17$
$x=4,y=1\implies z=20$

Other values of $x$ and $y$ give $z$ that is greater than 20. So the set is
\[
R=\{(1,1,5),(1,2,9),(1,3,13),(1,4,17),(2,1,8),(2,2,12),(2,3,16),(2,4,20),(3,1,13),(3,2,17),(4,1,20)\}.
\]

For the future, please see https://mathhelpboards.com/rules/ 11 (click "Expand" in the beginning).
 
Greetings, I am studying probability theory [non-measure theory] from a textbook. I stumbled to the topic stating that Cauchy Distribution has no moments. It was not proved, and I tried working it via direct calculation of the improper integral of E[X^n] for the case n=1. Anyhow, I wanted to generalize this without success. I stumbled upon this thread here: https://www.physicsforums.com/threads/how-to-prove-the-cauchy-distribution-has-no-moments.992416/ I really enjoyed the proof...

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