Answer:for ax^2+bx+c=0 the discriminant is b^2-4ac
there are 3 basic cases of what happens for different discriminants
1. if the discriminant is less than 0, then there are no real zeroes
2. if the discriminant is 0, then it has 1 zero
3. if the discriminant is greater than 0, it has 2 zeroes
so given
0=3x^2-7x+4
a=3,b=-7,c=4
thus the discriminant is (-7)^2-4(3)(4)=49-48=1
the discriminant is 1. 1 is positive, thus the equation has 2 zeroes because the discriminant is greater than 0
the answer is the equation has two zeroes because the discriminant is greater than 0
Step-by-step explanation:
The trigonometric identity can be used to solve for the height of the blue ladder that is leaning against the building is 
.
We have to determine
Which trigonometric identity can be used to solve for the height of the blue ladder that is leaning against the building?.
<h3>Trigonometric identity</h3>
Trigonometric Identities are the equalities that involve trigonometry functions and hold true for all the values of variables given in the equation.
Trig ratios help us calculate side lengths and interior angles of right triangles:
The trigonometric identity that can be used to solve for the height of the blue ladder is;
Hence, the trigonometric identity can be used to solve for the height of the blue ladder that is leaning against the building is .
To know more about trigonometric identity click the link given below.
brainly.com/question/1256744
Answer:
hey i think you forgot to add the expression, would u mind adding the question :) thanks
Step-by-step explanation:
Answer:
e) The mean of the sampling distribution of sample mean is always the same as that of X, the distribution from which the sample is taken.
Step-by-step explanation:
The central limit theorem states that
"Given a population with a finite mean μ and a finite non-zero variance σ2, the sampling distribution of the mean approaches a normal distribution with a mean of μ and a variance of σ2/N as N, the sample size, increases."
This means that as the sample size increases, the sample mean of the sampling distribution of means approaches the population mean. This does not state that the sample mean will always be the same as the population mean.
