Answer: B and E
Step-by-step explanation:
A polynomial is an algebraic expression of degree one variable and above.
A polynomial does not have negative in it exponent and cannot be divided by a variable.
Polynomial operations are addition, subtraction and multiplication. It also involves non-negative integer exponents of variables.
From the options given to you, only B and E are polynomials
Answer:
<em><u /></em>
- <em><u>A. Draw a diameter of the circle. </u></em>
Explanation:
To<em> draw a square</em> you can <em>draw a circle</em> with a <em>compass</em> and then construct the inscribed square.
You can construct an inscribed square with a compass and a straightedge.
The <u>first step</u> is to draw the circle.
The <u>next</u> step is to <em>draw a diameter</em> (any line that passes through the center of the circle, which you marked when drew the circle). Hence, this is the correct answer to the queston, and it is described by the choice A.
After that, you will be able to draw the perpendicular bisector of the diameter. The two diameters drawn will mark four equidistant points on the circle which will be the four vertices of your square.
Finally, you just must join the adjacent vertices with the straightedge.
Type I error says that we suppose that the null hypothesis exists rejected when in reality the null hypothesis was actually true.
Type II error says that we suppose that the null hypothesis exists taken when in fact the null hypothesis stood actually false.
<h3>
What is
Type I error and Type II error?</h3>
In statistics, a Type I error exists as a false positive conclusion, while a Type II error exists as a false negative conclusion.
Making a statistical conclusion still applies uncertainties, so the risks of creating these errors exist unavoidable in hypothesis testing.
The probability of creating a Type I error exists at the significance level, or alpha (α), while the probability of making a Type II error exists at beta (β). These risks can be minimized through careful planning in your analysis design.
Examples of Type I and Type II error
- Type I error (false positive): the testing effect says you have coronavirus, but you actually don’t.
- Type II error (false negative): the test outcome says you don’t have coronavirus, but you actually do.
To learn more about Type I and Type II error refer to:
brainly.com/question/17111420
#SPJ4
Answer:
not solvable
Step-by-step explanation:
so there is a ratio of 5:3
that equals 8 parts
if you divide 60 by 8 that's 7.5
times 7.5 by 5 and you get 37.5
don't know how u get half a person but that's just how it is
For each answer, we can plug in the given points:
A) is technically the same as B), but B) expresses correct function notation.
B) 5 = 5(1)
⇒ 5 = 5
25 = 5(2) ⇒ 25 ≠ 10
B) is incorrect.
C) I'm not sure what you mean y=5^5=x, but I'm going to use
because it's close to what you wrote:
The function
works for the points given.
D) 5 = 1 + 5 ⇒ 5 ≠ 6
D) is not correct.
Please check your functions; I'm not sure that C) is a function. In any case, the answer is C) because all the other answers are wrong.
