Does anybody have an answer for this right away!!!

. 5.8x10 to the power of 7

Delvig [45]

PEMDAS means we do exponents before we multiply.

10 ^ 7 = 10,000,000

(10 * 10 * 10 * 10 * 10 * 10 * 10)

5.8 * 10,000,000

= 58,000,000

4 0

3 years ago

The power generated by an electrical circuit (in watts) as a function of its current ccc (in amperes) is modeled by: P(c)=-20(c-

alekssr [168]

Answer:

The current that produces maximum power is 3A

Step-by-step explanation:

Given

$P(c) = 20(c - 3)^2$

Required [Missing from the question]

The current that produces maximum power

First, we represent the function in standard form

$P(c) = 20(c - 3)^2$

$P(c) = 20(c - 3)(c - 3)$

Open bracket

$P(c) = 20(c^2 -6c+ 9)$

$P(c) = 20c^2 -120c+ 180$

The maximum value of c is:

$Max(c) = \frac{-b}{2a}$

Where:

$f(x) = ax^2 + b^2 + c$

By comparison: $P(c) = 20c^2 -120c+ 180$

$a = 20$

$b = -120$

$c = 180$

So, we have:

$Max(c) = \frac{-b}{2a}$

$Max(c) = \frac{-(-120)}{2 * 20}$

$Max(c) = \frac{120}{40}$

$Max(c) = 3$

5 0

3 years ago

If the probability of rain is 0.87, what is the probability of NO rain?

maks197457 [2]

The probability of no rain is .13 Probability should add up to 1.00 (100%)

3 0

3 years ago

Two schools had a track and field competition. One school took 3,784 students. The other school

kati45 [8]

Answer:

4527

Step-by-step explanation:

total amount students = 4527+1641

=6168

amount of students who did not win a medal = total - amount who won a medal

= 6168-1641

=4527

3 0

3 years ago

Suppose babies born in a large hospital have a mean weight of 3242 grams, and a standard deviation of 446 grams. If 107 babies a

777dan777 [17]

Answer:

64.76% probability that the mean weight of the sample babies would differ from the population mean by less than 40 grams

Step-by-step explanation:

To solve this question, we have to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$