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irina1246 [14]
3 years ago
12

No question hahahaeuayeuqjhdws

Mathematics
1 answer:
goblinko [34]3 years ago
8 0

Answer: hahahaeuayeuqjhdws

Step-by-step explanation:

No question=hahahaeuayeuqjhdws

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PLEASE ANSWER ASAP!! e)What is the measure of ∠I? Explain
Zina [86]

Answer:

60^{\circ}

Step-by-step explanation:

From the given figure it is clear that the stop board is a regular hexagon and ∠I is an exterior angle of the regular hexagon.

Exterior angle of a regular polygon with n sides =\dfrac{360^{\circ}}{n}

In a regular hexagon number of sides: n =6

Exterior angle of a regular hexagon =\dfrac{360^{\circ}}{6}=60^{\circ}

Since ∠I is an exterior angle of the regular hexagon, therefore, \angle I=60^{\circ}.

4 0
3 years ago
5.5 divided by 83 in quotient
sammy [17]

the answer is 15.090090

7 0
3 years ago
Why is it important to choose a bank that is a member of the FDIC?
Anettt [7]
<span>Why is it important to choose a bank that is a member of the FDIC?

</span><span>The FDIC is a government bureau that insures the money that customers deposit in the bank, so your money is safer in an FDIC bank.

Hope This Helped! :3</span>
8 0
3 years ago
Read 2 more answers
Sam bought an electric iron as a price of 25 less than the original price if the original price of it is $2500 at what price did
wlad13 [49]

Answer:

$2475  or $1875

Step-by-step explanation:

Assuming the question meant to say $25 less than the original price, it would be $2475 because $2500-$25= $2475

However, if the question meant to say that Sam bought the iron for 25% less than the original price, it would be $1875 because 2500*0.25= $625

$2500-$625= $1875

4 0
3 years ago
A set of bivariate data was used to create a least squares regression line. Which of the following is minimized by the line
77julia77 [94]

Answer:

B) The sum of the squared residuals

Step-by-step explanation:

Least Square Regression Line is drawn through a bivariate data(Data in two variables) plotted on a graph to explain the relation between the explanatory variable(x) and the response variable(y).

Not all the points will lie on the Least Square Regression Line in all cases. Some points will be above line and some points will be below the line. The vertical distance between the points and the line is known as residual. Since, some points are above the line and some are below, the sum of residuals is always zero for a Least Square Regression Line.

Since, we want to minimize the overall error(residual) so that our line is as close to the points as possible, considering the sum of residuals wont be helpful as it will always be zero. So we square the residuals first and them sum them. This always gives a positive value. The Least Square Regression Line minimizes this sum of residuals and the result is a line of Best Fit for the bivariate data.

Therefore, option B gives the correct answer.

5 0
3 years ago
Read 2 more answers
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