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!
Answer:
0.4
Step-by-step explanation:
1/4 = 0.25
10
Step-by-step explanation:
Step-by-step explanation:
(1) Factor the GCF out of the trinomial on the left side of the equation. (2 points: 1 for the GCF, 1 for the trinomial) 2x²+6x-20=0
2x²+6x-20
2(x²+3x-10)
the factors are 2 and (x²+3x-10)
(2) Factor the polynomial completely. (4 points: 2 point for each factor)
2(x²+3x-10)
2(x²-2x+5x-10)
2(x(x-2) + 5(x-2)) group like terms
2(x+5)(x-2)
(3) If a product is equal to zero, we know at least one of the factors must be zero. And the constant factor cannot be zero. So set each binomial factor equal to 0 and solve for x, the width of your project. (2 points: 1 point for each factor)
constant = 2 cannot be zero
the other factors are (x+5) and (x-2)
(x+5)=0 => x= -5
or
(x-2)=0 => x=2
(4) What are the dimensions of your project? Remember that the width of your project is represented by x. (2 points: 1 point for each dimension)
thank you so much, sorry if it's a little confusing!!
(it is indeed confusing, because physical dimensions cannot be negative)
The dimensions of the project (assumed a rectangle) are +2 and -5
