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3 years ago

Exponent Rules Practice Multiplication Part 1: Simplity each expression. 1.) 23. 24

Mathematics

1 answer:

9966 [12]3 years ago

3 0

Answer:

2^7.

Step-by-step explanation:

2^3 * 2^4

= 2^(3+4)

= 2^7.

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The cost of 8 tacos is $6.00 at henry's food truck. what would be the cost of 13 tacos at the food truck?

saw5 [17]

$9.75 because one taco is 0.75 and 13 x 0.75 is $9.75

4 0

3 years ago

Which best describes the relationship between the two triangles below?

Nostrana [21]

Answer:

They are SIMILAR triangles

Step-by-step explanation:

Given triangles MNL and FHG with two of their angles to be 51° and 36° respectively. Their third angle is expressed as:

180°-(51°+36°)

= 180°-87°

= 93°

Their third angle is 93°

Since both triangles have the same angles in them, both triangles are considered as similar triangle even though the value of their sides are different due to angle differences in both.

Note that individual triangles are scalene triangles since their angles are not the same but the both triangles are similar triangles based on their relationship.

3 0

3 years ago

Please help with this question.

andrew11 [14]

Answer:

p3+13=37

We move all terms to the left:

p3+13-(37)=0

We add all the numbers together, and all the variables

p^3-24=0

7 0

3 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 ≈<u> -0.969</u>

<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

∑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;

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