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GenaCL600 [577]
3 years ago
5

M(5, 7) is the mid-point of the l.ine segment joining A (3,4) to B. Find the coordinates of B.

Mathematics
1 answer:
Nina [5.8K]3 years ago
5 0

Answer:

B(7,10)

Step-by-step explanation:

M(5,7)=(x ,y)\\A(3,4)=(x_1,y_1)\\B(x_2,y_2)\\\\Endpoint ;\\x = \frac{x_1+x_2}{2}\\ \\5 = \frac{3+x_2}{2}\\ Cross\:Multiply\\5\times 2 =3+x_2\\10=3+x_2\\10-3 =x_2\\7=x_2\\\\\\y = \frac{y_1+y_2}{2} \\\\7 = \frac{4+y_2}{2}\\ Cross\:Multiply\\7\times 2 =4+y_2\\14 =4+y_2\\14-4 =y_2\\10 =y_2\\\\\\B(7,10)

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Step-by-step explanation:

ΔLKM is an equilateral because a triangle with all 3 sides that are congruent is an equilateral triangle.

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<h3>Methods by which the line of best fit is found</h3>

The given data is presented in the following tabular format;

\begin{tabular}{|c|c|c|c|c|c|c|c|c|}Cost, (dollars), x&20&21&22&24&25&27&28&30\\Daily attendance, y&940&935&940&925&920&905&910&890\end{array}\right]

The equation of the line of best fit is given by the regression line

equation as follows;

  • \hat Y = \mathbf{b_0 + b_1 \cdot X_i}

Where;

\hat Y = Predicted value of the<em> i</em>th observation

b₀ = Estimated regression equation intercept

b₁ = The estimate of the slope regression equation

X_i = The <em>i</em>th observed value

b_1 = \mathbf{\dfrac{\sum (X - \overline X) \cdot (Y - \overline Y) }{\sum \left(X - \overline X \right)^2}}

\overline X = 24.625

\overline Y = 960.625

\mathbf{\sum(X - \overline X) \cdot (Y - \overline Y)} = -433.125

\mathbf{\sum(X - \overline X)^2} = 87.875

Therefore;

b_1 = \mathbf{\dfrac{-433.125}{87.875}} \approx -4.9289

Therefore;

  • The slope given to the nearest tenth is b₁ ≈ -4.9

b_0 = \mathbf{\dfrac{\left(\sum Y \right) \cdot \left(\sum X^2 \right) - \left(\sum X \right) \cdot \left(\sum X \cdot Y\right)} {n \cdot \left(\sum X^2\right) - \left(\sum X \right)^2}}

By using MS Excel, we have;

n = 8

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∑Y = 7365

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∑X·Y = 180930

(∑X)² = 38809

Therefore;

b_0 = \dfrac{7365 \times 4939-197 \times 180930}{8 \times 4939 - 38809} \approx \mathbf{1041.9986}

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The correlation coefficient given to the nearest thousandth is therefore;

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