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2 years ago

Solve the system of equations. y= 3x +5 y= 8x +3

Mathematics

2 answers:

Lady bird [3.3K]2 years ago

5 0

Answer:

y=6.2 and x=0.4 or (0.4,6.2)

Step-by-step explanation:

Since both expressions are equal to y, we can set them equal to each other and solve for x:

3x+5=8x+3

5=5x+3

2=5x

2/5=x

0.4=x

Now to solve y:

y=8(2/5)+3

y=16/5+3

y=3.2+3

y=6.2

Check answers:

6.2=3(0.4)+5

6.2=1.2+5

6.2=6.2

6.2=8(0.4)+3

6.2=3.2+3

6.2=6.2

Answers work, so y=6.2 and x=0.4 or (0.4,6.2) as an ordered pair

Ede4ka [16]2 years ago

5 0

Answer: x= 2/5 , y= 31/5

Step-by-step explanation:Let's work to solve this system of equations:

y= 3x +5 : Equation 1

y= 8x +3 : Equation 2

The tricky thing is that there are two variables, x and y. If only we could get rid of one of the variables...

subsitute y= 8x +3 : [8x+3=3x+5]

isolate x for 8x+3=3x+5: x+2/5

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Sin(-136°)=___. 1. sin (-316°) 2. -sin 44° 3. -sin 316° 4. -cos 44°

abruzzese [7]

Answer:

Step-by-step explanation:

sin (-136)=-sin 136=-sin(180-44)=-sin 44°

6 0

2 years ago

#10 i The table shows the admission costs (in dollars) and the average number of daily visitors at an amusement park each the pa

lions [1.4K]

The line of best fit is a straight line that can be used to predict the

average daily attendance for a given admission cost.

Correct responses:

The equation of best fit is; $\underline{ \hat Y = 1,042 - 4.9 \cdot X_i}$

The correlation coefficient is; r ≈ -0.969

<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 ith observation

b₀ = Estimated regression equation intercept

b₁ = The estimate of the slope regression equation

$X_i$ = The ith 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

∑X = 197

∑Y = 7365

∑X² = 4939

∑Y² = 6782675

∑X·Y = 180930

(∑X)² = 38809

Therefore;

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

The y-intercept given to the nearest tenth is b₀ ≈ 1,042

The equation of the line of best fit is therefore;

$\underline{\hat Y = 1042 - 4.9 \cdot X_i}$

The correlation coefficient is given by the formula;

$\displaystyle r = \mathbf{\dfrac{\sum \left(X_i - \overline X) \cdot \left(Y - \overline Y \right)}{ \sqrt{\sum \left(X_i - \overline X \right)^2 \cdot \sum \left(Y_i - \overline Y \right)^2} }}$