Ask question

Ask question

All categories

stealth61 [152]

3 years ago

8

If the sum of the expressions in Column A is equal to the sum of the expressions in Column B, what is the value of x? (will give

brainiest)

1 answer:

masha68 [24]3 years ago

4 0

X = 5

here is the work:

You might be interested in

Show me how to find x using the correct equation shown here (geometry)

scoundrel [369]

Answer:

13

Step-by-step explanation:

Angles ( 12x - 29 ) and ( 4x + 1 ) are co - interior angles.

Sum of co - interior angles is supplementary.

12x - 29 + 4x + 1 = 180

12x + 4x - 29 + 1 = 180

16x - 28 = 180

16x = 180 + 28

16x = 208

x = 208 / 16

x = 13

7 0

2 years ago

a population is growing continuously at a rate of 5%. if the population is now 3400, what will it be in 17 years?

DedPeter [7]

Answer:

7793

Step-by-step explanation:

3400 x 1.05^17 = 7792.862

6 0

3 years ago

Read 2 more answers

To prove that the triangles are similar by the SSS similarity theorem, which other sides or angles should be used?]

Margarita [4]

Answer: $\overline{MN}$ and $\overline{QR}$

Step-by-step explanation:

Given: In ΔMNO and ΔQRS

$\frac{SQ}{OM}=\frac{SR}{ON}=4$

To prove that the triangles are similar by the SSS similarity theorem [corresponding sides of similar triangles are proportional], there must be the third pair of corresponding sides,

That must be $\overline{MN}$ and $\overline{QR}$

such that $\frac{QR}{MN}=4$

3 0

3 years ago

Read 2 more answers

-5x2(2) + (-2)(2) what is the answer

Tema [17]

Answer:

The answer will be -24 :))

4 0

3 years ago

Let X1, . . . ,Xn be an i.i.d. random sample from a N(0, 1) population. Define Y1 = 1 n n X i=1 Xi , Y2 = 1 n n X i=1 |Xi| . Cal

nalin [4]

For each $1\le i\le n$ , $E[X_i]=0$ , so that

$\displaystyle E[Y_1]=E\left[\frac1n\sum_{i=1}^nX_i\right]=\frac1n\sum_{i=1}^nE[X_i]=0$

Meanwhile,

$\displaystyle E[Y_2]=\frac1n\sum_{i=1}^nE[|X_i|]$

Each of the $X_i$ have PDF

$f_{X_i}(x)=\dfrac1{\sqrt{2\pi}}e^{-x^2/2}$

for $x\in\Bbb R$ . From this we get

$E[|X_i|]=\displaystyle\frac1{\sqrt{2\pi}}\int_{-\infty}^\infty|x|e^{-x^2/2}\,\mathrm dx=\sqrt{\frac2\pi}\int_0^\infty xe^{-x^2/2}\,\mathrm dx=\sqrt{\frac2\pi}$

$\implies E[Y_2]=n\sqrt{\dfrac2\pi}$

8 0

3 years ago