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#10 i The table shows the admission costs (in dollars) and the average number of daily visitors at an amusement park each the past 8 years 8 year for Cost (dollars), x 20 21 22 24 25 27 28 30 Daily Attendance, y 940 935 940 925 920 905 910 890 Find an equation of the line of best fit. Round the slope and the y-intercept to the nearest tenth, if necessary. y = Identify the correlation coefficient. Round your answer to the nearest thousandths.​

Respuesta :

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; [tex]\underline{ \hat Y = 1,042 - 4.9 \cdot X_i}[/tex]
  • The correlation coefficient is; r ≈ -0.969

Methods by which the line of best fit is found

The given data is presented in the following tabular format;

[tex]\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][/tex]

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

equation as follows;

  • [tex]\hat Y = \mathbf{b_0 + b_1 \cdot X_i}[/tex]

Where;

[tex]\hat Y[/tex] = Predicted value of the ith observation

b₀ = Estimated regression equation intercept

b₁ = The estimate of the slope regression equation

[tex]X_i[/tex] = The ith observed value

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

[tex]\overline X[/tex] = 24.625

[tex]\overline Y[/tex] = 960.625

[tex]\mathbf{\sum(X - \overline X) \cdot (Y - \overline Y)} = -433.125[/tex]

[tex]\mathbf{\sum(X - \overline X)^2} = 87.875[/tex]

Therefore;

[tex]b_1 = \mathbf{\dfrac{-433.125}{87.875}} \approx -4.9289[/tex]

Therefore;

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

[tex]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}}[/tex]

By using MS Excel, we have;

n = 8

∑X = 197

∑Y = 7365

∑X² = 4939

∑Y² = 6782675

∑X·Y = 180930

(∑X)² = 38809

Therefore;

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

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

The equation of the line of best fit is therefore;

  • [tex]\underline{\hat Y = 1042 - 4.9 \cdot X_i}[/tex]

The correlation coefficient is given by the formula;

[tex]\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} }}[/tex]

Where;

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

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

Which gives;

[tex]r = \dfrac{-433.125}{446.8121} \approx \mathbf{-0.969367213}[/tex]

The correlation coefficient given to the nearest thousandth is therefore;

  • Correlation coefficient, r ≈ -0.969

Learn more about regression analysis here:

https://brainly.com/question/14279500