All Answers 358149 Answers

This sound like you are ribbing us. 

Happy birthday Dragonslayer

How come you not get any presents or a cake?

I though only Santa Claus have a naughty and nice list.

Maybe you were put on the SOL list hahaha

Thanks Chris, but I want an edible cake. Just kidding. nice bannana orange guy

Hi DragonSlayer554,

I am sorry you didn't get a real cake and real presents   

BUT

I gave you a birthday cake on your birthday

I even backed it up with a private message to make sure you would see it !

8 + 4 (3.5) =

8 + 14  =

22

H - A - P - P - Y       B - I  - R - T - H - D - A - Y,  

H - A - Y - L - E - Y  ...........!!!!!!!!!

We're glad you're still with us, DS.....!!!

Here's your cake......

Happy Birthday Hayley! :)

First, get the slope  = m =  [6 - 4] / [ 4 - 3]  =  [2] / [1]   = 2

Using this and one of the points - I'll choose (3,4) -  we can write

y - y₁  = m(x - x₁)

y - 4 = 2 (x - 3)

y = 2x - 6 + 4

y = 2x - 2       and that's in slope-intercept form

Hayley this is calculus

I'm not on my computer and I cannot think of the right words.

I don't think you can integrate it as such because it has a point at x=0.

However if you want the area under the curve do it from 0 to infinity (dropping the absolute sign) and double the answer.

I don't think that is hard. :/

What would you like to solve for?

YES.    :)

i^2 = -1

That was an excellent question !

22 = 15 + x

Subtract 15 from both sides of the equals sign

22 - 15 = 7

15 + x - 15 = x

so

7 = x

and

22 = 15 + 7

\(z =(−1 + i )^(1/3)\)

\(r=\sqrt((-1)^2+1^2)\)

\(r=\sqrt(1+1^2)\)

\(r=\sqrt(1+1)\)

\(r=\sqrt(2)\)

\(tan(\Theta)=1/-1\)

\(tan(\Theta)=-1\)

\(\Theta=tan^-1(-1)\)

\(\Theta=-\pi/4\)

\(\sqrt(2)e^(-\pi/4i)^(1/3)\)

\(\sqrt(2)^(1/3)e^(-\pi/12i)\)

\(\sqrt(2)^(1/3)*(cos(-\pi/12)+isin(-\pi/12))\)

\(\sqrt(2)^(1/3)*(0.965925826289 +isin(-\pi/12))\)

\(\sqrt(2)^(1/3)*(0.965925826289 +i*-0.258819045103)\)

\(\ 1.414213562373095)^(1/3)*(0.965925826289 +i*-0.258819045103)\)

\(\ 1.122462048309373*(0.965925826289 +i*-0.258819045103)\)

\(\ 1.084215081491274550528506797 +i*-0.290514555507789375384650419\)

\(\ 1.084215081491274550528506797 + -0.290514555507789375384650419i\)

Answer 1:\(\ 1.084215081491274550528506797 -0.290514555507789375384650419i\)

\(\sqrt(2)e^(7\pi/4i)^(1/3)\)

\(\sqrt(2)^(1/3)e^(7\pi/12i)\)

\(\sqrt(2)^(1/3)*(cos(7\pi/12)+isin(7\pi/12))\)

\(\sqrt(2)^(1/3)*(-0.258819045103 +isin(7\pi/12))\)

\(\sqrt(2)^(1/3)*(-0.258819045103 +i* 0.965925826289)\)

\(\ 1.414213562373095)^(1/3)*(-0.258819045103 +i* 0.965925826289)\)

\(\ 1.122462048309373*(-0.258819045103 +i* 0.965925826289)\)

\(\ -0.290514555507789375384650419 +i* 1.084215081491274550528506797\)

Answer 2:\(\ -0.290514555507789375384650419 +1.084215081491274550528506797i\)

\(\sqrt(2)e^(15\pi/4i)^(1/3)\)

\(\sqrt(2)^(1/3)e^(15\pi/12i)\)

\(\sqrt(2)^(1/3)*(cos(15\pi/12)+isin(15\pi/12))\)

\(\sqrt(2)^(1/3)*(-0.707106781187 +isin(15\pi/12))\)

\(\sqrt(2)^(1/3)*(-0.707106781187 +i* -0.707106781187)\)

\(\ 1.414213562373095)^(1/3)*(-0.707106781187 +i* -0.707106781187)\)

\(\ 1.122462048309373*(-0.793700525984607637192165751 +i* -0.793700525984607637192165751)\)

\(\ -0.793700525984607637192165751 +i*-0.793700525984607637192165751\)

\(\ -0.793700525984607637192165751 +-0.793700525984607637192165751i\)

Answer 3:\(\ -0.793700525984607637192165751 -0.793700525984607637192165751i\)

YOU TOO

i am a star wars fan :)

\(\sqrt(12.5(12.5-8)(12.5-10)(12.5-7))\)

\(\sqrt(12.5(4.5)(12.5-10)(12.5-7))\)

\(\sqrt(12.5(4.5)(2.5)(12.5-7))\)

\(\sqrt(12.5(4.5)(2.5)(5.5))\)

\(\sqrt(56.25(2.5)(5.5))\)

\(\sqrt(140.625(5.5))\)

\(\sqrt(773.4375)\)

\(27.8107443266087361 & -27.8107443266087361\)

5-x-2=3+4x+5     simplify both sides

3 - x  = 8 + 4x     add x to both sides, subtract 8 from both sides

-5  = 5x              divide both sides by 5

-1  = x 

The slope of a regression line (b) represents the rate of change in y as x changes. Because y is dependent on x, the slope describes the predicted values of y given x. When using the ordinary least squares method, one of the most common linear regressions, slope, is found by calculating b as the covariance of x and y, divided by the sum of squares (variance) of x, 

Remember from algebra, that the slope is the “m” in the formula y = mx + b.
In the linear regression formula, the slope is the a in the equation y’ = b + ax.

:D

Evaluate .1=.9^x take the log of both sides,

x=log(.1) / log(.9)

x=21.85434........

.1 = .9^x        take the log of both sides

log(0 1) =   log (0.9)^x        and we can write

log (0.1) = x * log (0.9)       divide both sides by log (0.9)

log (0.1)  / log (0.9)  =   x   = about  21.854

Wait. . so what are you asking?

Thank you, you too :)

Same to you,  twisted2017.......!!!