Answer:
x= 0 , 
, 
Step-by-step explanation:
Given, equation is ![\sqrt[3]{15x-1}](https://tex.z-dn.net/?f=%5Csqrt%5B3%5D%7B15x-1%7D)
+ ![\sqrt[3]{13x+1}](https://tex.z-dn.net/?f=%5Csqrt%5B3%5D%7B13x%2B1%7D)
= ![4\sqrt[3]{x}](https://tex.z-dn.net/?f=4%5Csqrt%5B3%5D%7Bx%7D)
. →→→ (1)
Now, by cubing the equation on both sides, we get
( + )³ = ()³
⇒ (15x-1) + (13x+1) + 3×× ( + ) = 64 x.
⇒ 28x + 3×× () = 64x.
(since from (1), + = )
⇒ 12× × (![\sqrt[3]{x}](https://tex.z-dn.net/?f=%5Csqrt%5B3%5D%7Bx%7D)
)= 36x.
⇒ 3x = ![\sqrt[3]{(15x-1)(13+1)(x)}](https://tex.z-dn.net/?f=%5Csqrt%5B3%5D%7B%2815x-1%29%2813%2B1%29%28x%29%7D)
.
Now, once again cubing on both sides, we get
(3x)³ = ()³.
⇒ 27x³ = (15x-1)(13x+1)(x).
⇒ 27x³ = 195x³ + 2x² - x
⇒ 168x³ + 2x² - x = 0
⇒ x(168x² + 2x -1) = 0
⇒ by, solving the equation we get ,
x = 0 ; x = ; x =
therefore, solution is x= 0 , ,
Which is 592/17 = 34.82 Rounding to the nearest tenth? Is 35.
Answer:
1 31/36 is your answer
Step-by-step explanation:
Find common denominators. Note that what you do to the denominator, you must do to the numerator;
(-7/18)(2/2) = (-14/36)
(-9/4)(9/9) = (-81/36)
Combine the terms:
(-14/36) - (-81/36)
Note that two negative signs directly next to each other equals a positive sign.
(-14/36) + 81/36
-14/36 + 81/36
(-14 + 81)/36
Combine like terms. Solve the parenthesis:
(67)/36
Change to a mixed fraction:
(67/36) = 1 31/36
1 31/36 is your answer.
~
Answer:
the slope of the regression equation for predicting our Exam 2 scores from Exam 1 scores is 0.492
And the y-intercept of the regression equation for predicting our Exam 2 scores from Exam 1 is 33.688
Step-by-step explanation:
Given the data in the question;
mean X" = 86
SD σx = 10
Y" = 76
SD σy = 8.2
r = 0.6
Here, Exam 2 is dependent and Exam 1 is independent.
The Regression equation is
y - Y" = r × σy/σx ( x - x" )
we substitute
y - 76 = 0.6 × 8.2/10 ( x - 86 )
y - 76 = 0.492( x - 86 )
y - 76 = 0.492x - 42.312
y = 0.492x - 42.312 + 76
y = 0.492x + 33.688
Hence, the slope of the regression equation for predicting our Exam 2 scores from Exam 1 scores is 0.492
And the y-intercept of the regression equation for predicting our Exam 2 scores from Exam 1 is 33.688
