The ratio of Sunita’s age to Mark’s age is currently 3 to 4, and in 12 years, it will be 5 to 6. What is Mark’s current age?

Janet and Nadia each play basketball, Nadia has won twice the number of games Janet has, Is it possible for Janet to have won 10

Lapatulllka [165]

Answer:

It is not possible for Janet to have won 10 games.

Step-by-step explanation:

Let be "x" the number of games Janet won.

We know that Nadia has won twice the number of games Janet has and the sum of the games Nadia and Janet have won together is 24.

Then, we express this situation with this equation:

So, let's check if it is possible for Janet to have won 10 games. Substitute into the expression:

Therefore, it is not possible for Janet to have won 10 games.

4 0

3 years ago

8(2x + 3) = PxQ

anyanavicka [17]

Respuesta:

P = 16; Q = 24

P = 0; Q = 0

Explicación paso a paso:

Dada la relación:

8 (2x + 3) = Px + Q

Abra el soporte

16x + 24 = Px + Q

Los valores de P y Q para los que la ecuación tiene infinidad de solución:

Px = 16x

Q = 24

Por tanto, en P = 16; Q = 24, la ecuación tiene infinidad de soluciones.

Valores de P y Q para los que la ecuación no tiene solución:

Px = 0; P = 0

Q = 0

Por tanto, los valores de P y Q para los que la ecuación no tiene solución es 0

5 0

3 years ago

I need help thank you

erma4kov [3.2K]

Answer:

≈ 5

Step-by-step explanation:

You can use the Pythagorean Theorem to solve this:

$a^{2} + b^{2} = c^{2}$

Now plug in the numbers into the formula:

$6^{2} + b^{2} = 8^{2}$

36 + $b^{2}$ = 64

Subtract 36 from both sides:

36 + $b^{2}$ = 64

-36 -36

_________

$b^{2}$ = 28

Square both sides:

$\sqrt{b^2} = \sqrt{28}$

b = 5.29

b ≈ 5

4 0

3 years ago

If two linear regression models have the same number of explanatory variables, a model with an R2 value of 0.45 is a better pred

icang [17]

Answer:

False

Step-by-step explanation:

Given that two linear regression models have the same number of explanatory variables

First model has coefficient of determination as 0.45 while other

0.65

we know that R^2 is the proportion showing the variation of dependent because of variation in independent variables.

Hence a higher R square is always better because it ensures more linearity and hence more accuracy in the regression equation.

Hence 0.65 model is better than 0.45 model.

The given statement is false.

5 0

3 years ago

Simplify : (√x + √y ) (√x − √y) (x + y)(x2 + y2)

Ivan

$Solution, \mathrm{Expand}\::\left(\sqrt{x}+\sqrt{y}\right)\left(\sqrt{x}-\sqrt{y}\right)\left(x+y\right)\left(x^2+y^2\right):\quad :x^4-:y^4$

$Steps:$

$\mathrm{Expand}\:\left(\sqrt{x}+\sqrt{y}\right)\left(\sqrt{x}-\sqrt{y}\right):\quad x-y, =\left(x-y\right)\left(x+y\right)\left(x^2+y^2\right)$

$\mathrm{Expand}\:\left(x-y\right)\left(x+y\right):\quad x^2-y^2, =:\left(x^2-y^2\right)\left(x^2+y^2\right)$

$\mathrm{Expand}\:\left(x^2-y^2\right)\left(x^2+y^2\right):\quad x^4-y^4, =:\left(x^4-y^4\right)$

$\mathrm{Expand}\::\left(x^4-y^4\right):\quad :x^4-:y^4, =:x^4-:y^4$

The correct answer is $x^4-y^4$

Hope this helps!!!

4 0

3 years ago