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stiv31 [10]
2 years ago
13

Help me with this pleaseee

Mathematics
1 answer:
matrenka [14]2 years ago
3 0
C, the remainder is 16.
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Find [4(cos15° + isin15°)]^3 and express it in a + bi form.
arsen [322]

Answer:

see explanation

Step-by-step explanation:

Using De Moivre's theorem

Given

[ 4(cos15° + isin15° ) ]³, then

= 4³ [ cos(3 × 15°) + isin(3 × 15°) ]

= 64 (cos45° + isin45° )

= 64 (\frac{\sqrt{2} }{2} + \frac{\sqrt{2} }{2} i )

= 64 (\frac{\sqrt{2} }{2} (1 + i) )

= 32\sqrt{2} (1 + i)

= 32\sqrt{2} + 32\sqrt{2} i

3 0
3 years ago
12 points !!! <br> Will mark brainliest <br> Help please
ss7ja [257]

Answer:

the 4th one

Step-by-step explanation:

3 0
2 years ago
What is 3 times the sum of x plus 2 is less than 10 as an inequality?
erica [24]
3(x+2) < 10 //// that should be right!!
7 0
3 years ago
Please someone help!
pochemuha
Your answer is 19 5/4
3 0
3 years ago
Read 2 more answers
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
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