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Lisa91
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How to prove that [tex] n^{\alpha} > \ln(n) [/tex] for [tex] \alpha>0 [/tex]?
ZaidAlyafey said:2-Now for n>1 :
${\alpha}\ln(n)> \ln(\ln(n)) \Rightarrow \,\, \alpha> \frac{\ln(\ln(n))}{\ln(n) } $
ILikeSerena said:Since the right hand side approaches zero for large n, this means that for any $\alpha>0$ there is a number N such that the inequality is true for any n > N.
ZaidAlyafey said:since $\alpha $ is an independent variable of n I can choose it as small as possible so that
it becomes lesser than the right-hand side .
Can you give a counter example for $\alpha$ and n that disproves my argument ?
This statement is an inequality that compares two mathematical expressions: n raised to the power of α and the natural logarithm of n. It states that for any positive value of α, the value of n raised to that power will always be greater than the natural logarithm of n.
This inequality is important because it helps us understand the relationship between exponential and logarithmic functions. It also has many practical applications in fields such as economics, physics, and computer science.
To prove this inequality, we can use mathematical induction, which is a method of proof that involves showing that a statement is true for a base case and then showing that if the statement is true for n, it must also be true for n+1. Using this method, we can prove that the inequality holds for all values of n and α greater than 0.
No, this inequality holds true for all positive values of n and α. It is a fundamental property of exponential and logarithmic functions.
One example is compound interest, where the value of an investment grows exponentially over time. Another example is population growth, where the size of a population increases exponentially. In both cases, the growth rate is greater than the natural logarithm of the initial value. This inequality also has practical applications in analyzing algorithms and their time complexities in computer science.