In a mountain range of Califormia, the percent of moisture that falls as snow rather than rain can be approximated by the function p(h) = 80 In (h) – 632, where h is the altitude in feet and p(h) is the percent of an annual snow fall at the altitude h. Use the function to approximate the amount of snow at the altitudes 3000 feet and 7000 feet. The percent of annual precipitation that falls as snow at 3000 feet is approximately %. (Round to the nearest integer.) The percent of annual precipitation that falls as snow at 7000 feet is approximately %. (Round to the nearest integer)
Minimization
In mathematics, traditional optimization problems are typically expressed in terms of minimization. When we talk about minimizing or maximizing a function, we refer to the maximum and minimum possible values of that function. This can be expressed in terms of global or local range. The definition of minimization in the thesaurus is the process of reducing something to a small amount, value, or position. Minimization (noun) is an instance of belittling or disparagement.
Maxima and Minima
The extreme points of a function are the maximum and the minimum points of the function. A maximum is attained when the function takes the maximum value and a minimum is attained when the function takes the minimum value.
Derivatives
A derivative means a change. Geometrically it can be represented as a line with some steepness. Imagine climbing a mountain which is very steep and 500 meters high. Is it easier to climb? Definitely not! Suppose walking on the road for 500 meters. Which one would be easier? Walking on the road would be much easier than climbing a mountain.
Concavity
In calculus, concavity is a descriptor of mathematics that tells about the shape of the graph. It is the parameter that helps to estimate the maximum and minimum value of any of the functions and the concave nature using the graphical method. We use the first derivative test and second derivative test to understand the concave behavior of the function.
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