Answer:
The probability is 2/7 or 28.57%
Step-by-step explanation:
we know that
The probability of an event is the ratio of the size of the event space to the size of the sample space.
The size of the sample space is the total number of possible outcomes
The event space is the number of outcomes in the event you are interested in.
so
Let
x------> size of the event space
y-----> size of the sample space
so
In this problem we have
---> number of peanuts
---> total number of items
substitute
Simplify
Convert to percentage
It is hard to see the picture.
We have 2 denominators that we need to get rid of. Whenever there are the denominators, all we have to do is multiply all whole equation with the denominators.
Our denominators are both 2 and x+1. Therefore, we multiply the whole equation by 2(x+1)
![\frac{x}{2}[2(x+1)]-\frac{2}{x+1}[2(x+1)] = 1[2(x+1)]](https://tex.z-dn.net/?f=%5Cfrac%7Bx%7D%7B2%7D%5B2%28x%2B1%29%5D-%5Cfrac%7B2%7D%7Bx%2B1%7D%5B2%28x%2B1%29%5D%20%3D%201%5B2%28x%2B1%29%5D)
Then shorten the fractions.
![\frac{x}{2}[2(x+1)]-\frac{2}{x+1}[2(x+1)] = 1[2(x+1)]\\x(x+1)-2(2)=1(2x+2)](https://tex.z-dn.net/?f=%5Cfrac%7Bx%7D%7B2%7D%5B2%28x%2B1%29%5D-%5Cfrac%7B2%7D%7Bx%2B1%7D%5B2%28x%2B1%29%5D%20%3D%201%5B2%28x%2B1%29%5D%5C%5Cx%28x%2B1%29-2%282%29%3D1%282x%2B2%29)
Distribute in all.
We should get like this. Because the polynomial is 2-degree, I'd suggest you to move all terms to one place. Therefore, moving 2x+2 to another side and subtract.
We are almost there. All we have to do is, solving for x by factoring. (Although there are more than just factoring but factoring this polynomial is faster.)
Thus, the answer is x = 3, -2
Answer:
At a level of 95%, it is expected that the interval [0.45; 11.59] contains the value of the ductility in steel when its carbon content is 0.5%.
Step-by-step explanation:
Hello!
Considering the dependent variable:
Y: Ductility in steel.
And the independent variable:
X: Carbon content of the steel.
The linear regression was estimated and a prediction interval was calculated.
The prediction interval is calculated to predict a value that the variable Y (response variable) can take for a given value of the variable X (predictor variable) in the definition range of the linear regression line. Symbolically [Y/X=
]
In this case 95% prediction interval for Y/X=0.5
At a level of 95%, it is expected that the interval [0.45; 11.59] contains the value of the ductility in steel when its carbon content is 0.5%.
I hope it helps!
A for #1
C for #2 ! Hope this helped you out!
