Since the equation is in y = mx+b form you can easily determine the y intercept based on the b value present.
Y = mx + b
Y = 2x - 3
B = y intercept = (0,-3).
Answer:
![Length=9.6 cm\\\\Width=4.8 cm](https://tex.z-dn.net/?f=Length%3D9.6%20cm%5C%5C%5C%5CWidth%3D4.8%20cm)
Step-by-step explanation:
Length=2*Width
L=2*W
Perimeter=28.8 cm
Perimeter of a rectangle= 2(Length+Width)
![28.8=2(2W+W)\\\\28.8=2(3W)\\\\3W=28.8/2\\\\3W=14.4\\\\W=14.4/3\\\\W=4.8 cm\\\\](https://tex.z-dn.net/?f=28.8%3D2%282W%2BW%29%5C%5C%5C%5C28.8%3D2%283W%29%5C%5C%5C%5C3W%3D28.8%2F2%5C%5C%5C%5C3W%3D14.4%5C%5C%5C%5CW%3D14.4%2F3%5C%5C%5C%5CW%3D4.8%20cm%5C%5C%5C%5C)
![Length=2*Width\\\\=2*4.8\\\\=9.6 cm\\\\](https://tex.z-dn.net/?f=Length%3D2%2AWidth%5C%5C%5C%5C%3D2%2A4.8%5C%5C%5C%5C%3D9.6%20cm%5C%5C%5C%5C)
![Length=9.6 cm\\\\Width=4.8 cm](https://tex.z-dn.net/?f=Length%3D9.6%20cm%5C%5C%5C%5CWidth%3D4.8%20cm)
Answer:
The answer is x²-9x+16
Step-by-step explanation:
Hello there.
Linear regression is a useful tool that allows calculating approximate values for a function that passes through given points(with the best error possible). It is very useful in science to make an estimation of the comportment of movement, electricity and some decays.
For example, I will relate a case in a physics lab: We calculated the positions of a car in an air rail and the times. With this information, I was able to make a linear regression to calculate the Position function for that case.
<h3>Answer: 0.47178 Step-by-step explanation:
Find the probability for each p(X=x) up to 5 using the equation: (x-1)C(r-1)*p^r * q^x-r,
where x is number of days, p = .3 (prob of rain). q=.7 (prob of not rain), and r=2 (second day of rain). also C means choose.
So p(X=1) = 0
p(X=2) = 1C1 * .3^2 * .7^0 = .09
P(X=3) = 2C1 * .3^2 * .7^1 = .126
P(X=4) = 3C1 * .3^2 * .7^2 = .1323
P(X=5) = 4C1 * .3^2 * .7^3 = .12348
Then add all of them up
0+.09+.126+.1323+.12348 = .47178</h3>