Can the relation a^p+b^p>=2c^p be proven for p values between 0 and 1?

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In summary, the conversation discusses the problem of finding values of p that satisfy the inequality a^p+b^p>=c^p for a+b>=c. It is noted that for p>1, the relation does not hold, but there is a question about whether it can be proved for p from the interval [0, 1]. The possibility of using the nth power of binomial a+b to solve the problem is mentioned, but the formula found is complicated and a simpler approach is sought. The problem is then stated precisely and it is noted that the inequality holds for p=0.5, but the question remains for other values of p.
  • #1
onako
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Given [tex] a+b >=c [/tex], I'm trying to obtain values of p such that [tex]a^p+b^p>=c^p[/tex]. Obviously,
for p>1 the relation does not work. However, I wonder if it can be proved that it works for p from the interval [0, 1].
I tried to solve this with the nth power of binomial a+b, but the formula I found is complicated. Perhaps you
have a much simpler approach to resolve the problem (either by disproving that the requirement is possible, or by proving the opposite)

Thanks
 
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  • #2
So, to state the problem precisely:
Assuming [tex] a+b>=2c[/tex] and [tex]a^p*b^p >= c^{2p}, p \in [0, 1][/tex]
can we prove that
[tex]
a^p+b^p>=2c^p
[/tex]
This holds for for p=0.5, but I wonder if this applies to the other values
0<p<1. Perhaps it is true for 0.5<=p<=1.

Thanks, I hope this clarified the problem. Please move the post to the appropriate math subforum.
 

FAQ: Can the relation a^p+b^p>=2c^p be proven for p values between 0 and 1?

What is the purpose of proving relation in science?

The purpose of proving relation in science is to establish a cause-and-effect relationship between two or more variables. This helps scientists understand how different factors may influence a particular phenomenon or outcome.

How do scientists go about proving a relation?

Scientists use various methods and techniques, such as experiments, statistical analysis, and observational studies, to prove a relation between variables. They carefully design their studies and collect data to test their hypotheses and draw conclusions.

What are some common challenges in proving a relation?

One common challenge in proving a relation is establishing a clear and direct link between cause and effect. Other challenges may include controlling for confounding variables, obtaining a sufficient sample size, and interpreting complex or contradictory data.

Can correlation be used to prove a relation?

No, correlation does not necessarily imply causation. While a strong correlation between two variables may suggest a potential relation, it does not prove that one variable causes the other. Further research and experimentation are needed to establish a cause-and-effect relationship.

What is the importance of replicating results in proving a relation?

Replicating results is essential in proving a relation because it helps to ensure the validity and reliability of the findings. If multiple studies can replicate the same results, it strengthens the evidence for a relation between variables.

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