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WITCHER [35]
2 years ago
11

Need help with this math 3 part question!!!

Mathematics
1 answer:
Illusion [34]2 years ago
4 0

Answer:

Step-by-step explanation:

bruh this looks hard.

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Pls help me I need it urgently but please give right answer
lina2011 [118]

Answer:

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2 years ago
Write two numbers that when rounded to the thousands place have an estimated sum of 10,000
m_a_m_a [10]
<span>Rounded numbers are easier to work with in your head. They are only approximate. An exact answer can not be obtained with these numbers. Sometimes an exact answer is not required.To round numbers to the nearest ten thousand, make the numbers whose last four digits are 0001 through 4999 into the next lower number that ends in 0000. For example 54,424 rounded to the nearest ten thousand would be 50,000. Numbers that have the last four digits of 5000 or more should be rounded up to the next even ten thousand. The number 78,988 rounded to the nearest ten thousand would be 80,000.this might help you understand 
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4 0
3 years ago
Joe deposit $4000 into an account that pays simple interest to rate of 2% per year how much interest would be paid in the first
fenix001 [56]
Answer is $240.00 because 2% of $4000 is 80. Multiply 80 by 3 years and you get $240.00
6 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
2 years ago
Read 2 more answers
CAN SOMEONE PLEASE HELP ME WITH THIS FUNCTION PROBLEM
ycow [4]

Answer:

Choose f(x) = 11x + 1

Step-by-step explanation:

Note that we will simply plug the value of 2 into the equation for February:

f(2) = 11(2) + 1 = 23

And plug the value of 6 into the equation for June:

f(6) = 11(6) + 1 = 67

Note how the points on the graph seem to match up with these values.  If we evaluate following the same style for each:

f(3) = 11(3) + 1 = 34

f(4) = 11(4) + 1 = 45

f(5) = 11(5) + 1 = 56

Note, these values seems to be very close in approximation to the graph points for each month.

The other three functions return values that are just to far away from what are represented in the graph.

Cheers.

8 0
3 years ago
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