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To predict the number of movie tickets sold in 2014 using the line of best fit equation:

1. The given equation is \( y = 20.68x - 40,040.07 \), where \( x \) is the year and \( y \) is the number of movie tickets sold (in millions).
2. For 2014, \( x = 2014 \).

Now, substitute \( x = 2014 \) into the equation:

\[
y = 20.68 \times 2014 - 40,040.07
\]

First, calculate \( 20.68 \times 2014 \):

\[
20.68 \times 2014 = 41,646.32
\]

Now, subtract \( 40,040.07 \) from \( 41,646.32 \):

\[
y = 41,646.32 - 40,040.07 = 1,606.25
\]

Rounding to the nearest whole number:

\[
y \approx 1,606
\]

Thus, the predicted number of movie tickets sold in 2014 is **1,606 million**.

Would you like further clarification or details?

Here are 5 questions for further exploration:
1. How is the line of best fit calculated using statistical methods?
2. What does the correlation coefficient \( r = 0.994 \) indicate about the relationship between the variables?
3. How does rounding impact predictions in mathematical models?
4. What is the significance of using past data to predict future trends in statistics?
5. How does the slope \( 20.68 \) affect the prediction for each year?

**Tip:** Always double-check calculations, especially when working with large numbers, to avoid rounding errors in predictions.

Use a graphing calculator to find the equation of the line of best fit for the data in the table below. Find the value of the correlation coefficient r. Then predict the number of movie tickets sold in 2014.

Learn how to use the equation of the line of best fit and the correlation coefficient to predict movie ticket sales in 2014. Includes step-by-step calculations and explanations, covering concepts such as linear regression and correlation.

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