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3 years ago

HELP ME PLEASE!!! I DON'T UNDERSTAND!

Mathematics

2 answers:

krek1111 [17]3 years ago

7 0

Answer:

I believe that the answer is 12 but find someone who knows for sure.

Rama09 [41]3 years ago

3 0

Answer: 12

Step-by-step explanation:

this is a right angled triangle so you use the pythagorean theory

which is a^2 + b^2 = c^2

you have c and b already. c is the hypotenuse.

a^2 + 16^2 = 20^2

a^2 + 256 = 400

a^2 = 400 - 256

a^2 = 144

then you square root 144 and get..

a = 12

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A number z is greater than or equal to –8 and is less than -5.

Zina [86]

Answer:

z ≥ -8 - (-5)

Step-by-step explanation:

5 0

4 years ago

1.) The deer population increases at a rate of 3% per year. There are 1253 deer this year. Write a function that models the deer

BabaBlast [244]

Exponential growth/decay rule with general function is:y=y(0)ekt with k is growth/decay constant rate.
(1) Deer population function y(0) = 1253 k
= 3% t
= 6 (years)
y(6) = 1253 . e^(0.03*6) ~ 1500 (deers)
: 1496 deers
(2) Growth factor b is rate 9.5% = 0.095

4 0

4 years ago

Read 2 more answers

A tattoo enthusiast website claims that :

KATRIN_1 [288]

Answer:

The probability that a person is a Millennial given that they have tattoos is 0.5069 (50.69%) or about 0.51 (51%).

Step-by-step explanation:

We have here a case where we need to use Bayes' Theorem and all conditional probabilities related. Roughly speaking, a conditional probability is a kind of probability where an event determines the occurrence of another event. Mathematically:

$\\ P(A|B) = \frac{P(A \cap B)}{P(B)}$

In the case of the Bayes' Theorem, we have also a conditional probability where one event is the sum of different probabilities.

We have a series of different probabilities that we have to distinguish one from the others:

The probability that a person has a tattoo assuming that is a Millennial is:

$\\ P(T|M) = 0.47$

The probability that a person has a tattoo assuming that is of Generation X is:

$\\ P(T|X) = 0.36$

The probability that a person has a tattoo assuming that is of Boomers is:

$\\ P(T|B) = 0.13$

The probability of being of Millennials is:

$\\ P(M) = 0.22$

The probability of being of Generation X is:

$\\ P(X) = 0.20$

The probability of being of Boomers is:

$\\ P(B) = 0.22$

Therefore, the probability of the event of having a tattoo P(T) is:

$\\ P(T) = P(T|M)*P(M) + P(T|X)*P(X) + P(T|B)*P(B)$

$\\ P(T) = 0.47*0.22 + 0.36*0.20 + 0.13*0.22$

$\\ P(T) = 0.204$

For non-independent events that happen at the same time, we can say that the probability of occurring simultaneously is:

$\\ P(M \cap T) = P(M|T)*P(T)$

$\\ P(T \cap M) = P(T|M)*P(M)$

But

$\\ P(M \cap T) = P(T \cap M)$

Then

$\\ P(M|T)*P(T) = P(T|M)*P(M)$

We are asked for the probability that a person is a Millennial given or assuming that they have tattoos or P(M | T). Solving the previous formula for the latter:

$\\ P(M|T)*P(T) = P(T|M)*P(M)$

$\\ P(M|T) = \frac{P(T|M)*P(M)}{P(T)}$

We have already know that

$\\ P(T|M) = 0.47\;P(M) = 0.22\;and\;P(T) = 0.204$ .

Therefore

$\\ P(M|T) = \frac{0.47*0.22}{0.204}$

$\\ P(M|T) = 0.50686 \approx 0.51$

Thus, the probability that a person is a Millennial given that they have tattoos is 0.5069 (50.69%) or about 0.51 (51%).

5 0

4 years ago

Walter chrysler sells car engines. He receives a 11% commission on the first $50,000 in sales and 17% on anything over $50000. H

Reika [66]

Answer
A
Explanation

3 0

3 years ago

He mean potassium content of a popular sports drink is listed as 140 mg in a 32-oz bottle. Analysis of 20 bottles indicates a sa

mezya [45]

Answer: (A) H0: μ = 140 mg vs. H1: μ ≠ 140 mg

Step-by-step explanation:

Usually null hypothesis represents the claim that the values associated to the groups being tested have no statistical difference but alternative hypothesis supports the claim that there is statistical difference.

Let $\mu$ be the population mean .

We are given that the mean potassium content of a popular sports drink is listed as 140 mg in a 32-oz bottle.

i.e. Null hypothesis : $H_0:\mu=140$

Alternative hypothesis for two tail hypothesis has sign (≠).

i.e. Alternative hypothesis : $H_1 : \mu\neq140$

∴ The hypotheses for a two-tailed test of the claimed potassium content:

H0: μ = 140 mg vs. H1: μ ≠ 140 mg

3 0

3 years ago