Choose the graph below that correctly represents the equation 2x + 4y = 24.

Mathematics

2 answers:

Effectus [21]3 years ago

6 0

Answer:

A Boiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii

Step-by-step explanation:

Vlad1618 [11]3 years ago

5 0

My answer is A (the first graph picture). Here is my explanation.

1. 2x = 24 - 4y (Move the variable to the right side and change the sign)
2. X = 12 - 2y (Divide both sides of the equation by 2)
3. Y = 6 and X = 12 (I used my graphing calculator and A is what I got)

Hope this helps, if not, then I apologize! :)

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What is the equation of the rational function g(x) and its corresponding slant asymptote?

bija089 [108]

The solution to the Questions are

The alternate hypothesis demonstrates that there are two possible outcomes for the test.

Decision rule: If z > 2.05 or z<-2.05, reject H0

z=2.59

The two-tailed nature of the test is shown by the alternative hypothesis.
The result of the test yields the following P-value: 0.0096

<h3>What is the alternate hypothesis?</h3>

(a)

The alternate hypothesis demonstrates that there are two possible outcomes for the test.

(b)

Here we have

$n_{1}=40,\\\\ \bar{x}_{1}=102,\sigma_{1}=5,n_{2}=50,\bar{x}_{2}=99,\sigma_{2}=6$

(b)

Here the test is two-tailed. So for $\alpha =0.04$ , the critical values of the z-test are -2.05 and 2.05.

Decision rule: If z > 2.05 or z<-2.05, reject H0

(c)

Test statistics will be

$z=\frac{(\bar{x}_{1}-\bar{x}_{2})-(\mu_{1}-\mu_{2})}{\sqrt{\frac{\sigma^{2}_{1}}{n_{1}}+\frac{\sigma^{2}_{2}}{n_{2}}}} \\\\\\z=\frac{(102-99)-(0)}{\sqrt{\frac{5^{2}}{40}+\frac{6^{2}}{50}}}$