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Sladkaya [172]
3 years ago
6

Please answer below thx.

Mathematics
1 answer:
slava [35]3 years ago
8 0

Answer:

24 cm

Step-by-step explanation:

since the two triangles are similar,

10cm/20cm = 36cm _ h/h

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F(x)= (x+1)/2
xeze [42]

9514 1404 393

Answer:

  g(f(x)) = x . . . so the functions are inverses

Step-by-step explanation:

Two functions f and g are inverses of each other if ...

  g(f(x)) = x   or   f(g(x)) = x

We are asked to evaluate g(f(x)). That will be x if the functions are inverses.

  g(f(x)) = g((x+1)/2) = 2((x +1)/2) -1 = (x +1) -1

  g(f(x)) = x . . . . the functions are inverses

4 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} }}

Where;

\sqrt{\sum \left(X - \overline X \right)^2 \times \sum \left(Y - \overline Y \right)^2}  = \mathbf{446.8121}

\sum \left(X_i - \overline X \right) \times \left(Y - \overline Y\right) = \mathbf{-433.125}

Which gives;

r = \dfrac{-433.125}{446.8121}  \approx \mathbf{-0.969367213}

The correlation coefficient given to the nearest thousandth is therefore;

  • <u>Correlation coefficient, r ≈ -0.969</u>

Learn more about regression analysis here:

brainly.com/question/14279500

7 0
3 years ago
SLFJ SDFNEFS LF A SF IE FJS VS IKF DSFNIS DSF
avanturin [10]

Answer:

40

Step-by-step explanation:

I think but what do you mean???!!!!

6 0
3 years ago
What is the value of x?<br> Enter your answer in the box.<br><br> x =
LUCKY_DIMON [66]

Answer: x = 39  because 39 + 102 = 141 and 180 -  141 = 39

7 0
3 years ago
(Once again) "find the value of x"
alukav5142 [94]

Answer:

15

Step-by-step explanation:

8 0
3 years ago
Read 2 more answers
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