In the table below, the number of pounds of blueberries is proportional to the number of pounds of strawberries.

Mathematics

2 answers:

dimaraw [331]3 years ago

8 0

the answer is A i think

AleksAgata [21]3 years ago

4 0

Answer:

A the answer is A

Step-by-step explanation:

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the probability density for a particle in a box is an oscillatory function even for very large energies. Explain how the classic

77julia77 [94]

Answer:

This is achieved for the specific case when high quantum number with low resolution is present.

Step-by-step explanation:

In Quantum Mechanics, the probability density defines the region in which the likelihood of finding the particle is most.

Now for the particle in the box, the probability density is also dependent on resolution as well so for large quantum number with small resolution, the oscillations will be densely packed and thus indicating in the formation of a constant probability density throughout similar to that of classical approach.

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3 years ago

If h(x) = 5x -7,find the h(14)

Mrac [35]

B. That is the correct answer because h(14) = 63 when you divide it by 3

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3 years ago

Audrey, an astronomer is searching for extra-solar planets using the technique of relativistic lensing. Though there are believe

Stolb23 [73]

Answer:

Step-by-step explanation:

The model $N (t)$ , the number of planets found up to time $t$ , as a Poisson process. So, the $N (t)$ has distribution of Poison distribution with parameter $(\lambda t)$

The mean for a month is, $\lambda = \frac{1}{3}$ per month

$E[N(t)]= \lambda t\\\\=\frac{1}{3}(24)\\\\=8$

(Here. t = 24)

For Poisson process mean and variance are same,

$Var[N (t)]= Var[N(24)]\\= E [N (24)]\\=8$

(Poisson distribution mean and variance equal)

The standard deviation of the number of planets is,

$\sigma( 24 )] =\sqrt{Var[ N(24)]}=\sqrt{8}= 2.828$

For the Poisson process the intervals between events(finding a new planet) have independent exponential distribution with parameter $\lambda$ . The sum of $K$ of these independent exponential has distribution Gamma $(K, \lambda)$ .