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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 Year Tickets Sold (millions) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1281 1300 1306 1321 1358 1380 1389 1416 1448 1454 Find the equation of the line of best fit. Round to two decimal places as needed. Choose the correct answer below O B. y= - 39,522.11 A. y= 20.42x - 39,522.11 O D. y= - 39,522.11x + 20.42 O C. y= 20.42x + 39,522.11 (Round to three decimal places as needed.) The correlation coefficientr is

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 Year Tickets Sold (millions) 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1281 1300 1306 1321 1358 1380 1389 1416 1448 1454 Find the equation of the line of best fit. Round to two decimal places as needed. Choose the correct answer below O B. y= - 39,522.11 A. y= 20.42x - 39,522.11 O D. y= - 39,522.11x + 20.42 O C. y= 20.42x + 39,522.11 (Round to three decimal places as needed.) The correlation coefficientr is

Calculus: Early Transcendentals
Calculus: Early Transcendentals
8th Edition
ISBN:9781285741550
Author:James Stewart
Publisher:James Stewart
Chapter1: Functions And Models
Section: Chapter Questions
Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...
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**Analyzing Movie Ticket Sales Over Time** In this activity, you will learn how to use a graphing calculator to find the equation of the line of best fit for historical movie ticket sales data. This process will also involve computing the correlation coefficient to measure the strength of the relationship between the variables. Finally, you'll use these calculations to predict the number of movie tickets that could be sold in the year 2014. **Data Table** | Year | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | |------|------|------|------|------|------|------|------|------|------|------| | Tickets Sold (millions) | 1281 | 1300 | 1306 | 1321 | 1358 | 1380 | 1389 | 1416 | 1448 | 1454 | **Task** Find the equation of the line of best fit. Round your answer to two decimal places. **Possible Answers** - A. \( y = 20.42x - 39,522.11 \) - B. \( y = -39,522.11 \) - C. \( y = 20.42x + 39,522.11 \) - D. \( y = -39,522.11x + 20.42 \) **Next Steps** - Calculate the correlation coefficient \( r \) and round it to three decimal places. - Use the line of best fit to predict the number of movie tickets sold in 2014. This exercise will help you understand how historical data can be used to make future predictions, emphasizing the importance of statistical tools in analysis.
Transcribed Image Text:**Analyzing Movie Ticket Sales Over Time** In this activity, you will learn how to use a graphing calculator to find the equation of the line of best fit for historical movie ticket sales data. This process will also involve computing the correlation coefficient to measure the strength of the relationship between the variables. Finally, you'll use these calculations to predict the number of movie tickets that could be sold in the year 2014. **Data Table** | Year | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | |------|------|------|------|------|------|------|------|------|------|------| | Tickets Sold (millions) | 1281 | 1300 | 1306 | 1321 | 1358 | 1380 | 1389 | 1416 | 1448 | 1454 | **Task** Find the equation of the line of best fit. Round your answer to two decimal places. **Possible Answers** - A. \( y = 20.42x - 39,522.11 \) - B. \( y = -39,522.11 \) - C. \( y = 20.42x + 39,522.11 \) - D. \( y = -39,522.11x + 20.42 \) **Next Steps** - Calculate the correlation coefficient \( r \) and round it to three decimal places. - Use the line of best fit to predict the number of movie tickets sold in 2014. This exercise will help you understand how historical data can be used to make future predictions, emphasizing the importance of statistical tools in analysis.
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