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3 years ago

PLEASE HELP!!!!!!!!!!!

1 answer:

6 0

For every One cup that Susan makes she has five strawberries and three kiwis. For every 1 cup that Joanna makes, there are eight strawberries. So now we have to figure out how many kiwi that are in her cup. So if there are eight strawberries we were going to add one for the kiwi and that will be nine. So for Joanna she uses eight strawberries and nine kiwis

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For which inequality would x = 8 not be a solution?4x + 3 > 09x - 5 < 100x + 4 ≤ 1072 ÷ x ≥ 4

galina1969 [7]

Given:

Given the inequalities:4

$\begin{gathered} 4x+3>0 \\ 9x-5$

Required: Identify the inequality in which x = 8 is a solution.

Explanation:

Substitute 8 for x in each inequality and check whether it satisfies the inequality.

Consider 4x + 3 > 0.

$4\cdot8+3=35>0$

So, x = 8 satisfies the inequality 4x + 3 > 0.

Consider 9x - 5 < 100.

$9\cdot8-5=67$

So, x = 8 satisfies the inequality 9x - 5 < 100.

Consider x + 4 ≤ 10.

$8+4=12>10$

So, x = 8 not satisfies the inequality.

Consider 72 ÷ x ≥ 4.

$72\div8=9\ge4$

So, x = 8 satisfies the inequality.

Final Answer: The inequality in which x = 8 is not a solution is x + 4 ≤ 10.

5 0

11 months 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;

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