Answer:
v(m) = 8 + 48m+ 180m² +216m³
Step-by-step explanation:
Let's first of all represent the edge of the the cube as a function of minutes.
Initially the egde= 2feet
As times elapsed , it increases at the rate of 6 feet per min, that is, for every minute ,there is a 6 feet increase.
Let the the egde be x
X = 2 + 6(m)
Where m represent the minutes elapsed.
So we Al know that the volume of an edge = edge³
but egde = x
V(m) = x³
but x= 2+6(m)
V(m) = (2+6m)³
v(m) = 8 + 48m+ 180m² +216m³
Answer:
348 degrees
Step-by-step explanation:
29 pi /15 to degrees
To change from radians to degrees, multiply by 180/pi
29 pi /15 * 180/pi
29 * 180/15
348
No, Leo's answer is not a product of prime polynomials because x2 – 1 can be factored. This is a difference of squares. He should continue factoring to get
(x – 1)(x + 1)(3x + 5).
Correct question
Sale Price :160 | 180 | 200 | 220 | 240 | 260 | 280
New home : 126 | 103 | 82 | 75 | 82 | 40 | 20
A.) state the linear regression function that estimates the number of new homes available at a specific price.
B.) state the correlation Coefficient of the data, and explain what it means in the context of the problem
Answer:
Y = -0.79X + 249.86
R = -0.9543
Step-by-step explanation:
Sale Price :160 | 180 | 200 | 220 | 240 | 260 | 280
New home : 126 | 103 | 82 | 75 | 82 | 40 | 20
Calculate the Linear regression equation :
Using the linear regression calculator :
The linear regression equation is :
Y = -0.79X + 249.86
The correlation Coefficient 'R' measures the strength of statistical relationship between the relative movement of two variables. The The value of R is -0.9543 in the question above.
This is a strong negative correlation, which means that high sales price of homes scores correlates with low number of new homes scores (and vice versa). Homes with high sales price have fewer number of new homes.