Notice that it is okay to enter the time as the actual years: 1998, 1999, and so on.
Line of Best Fit: y=21.4x-41 557 Correlation Coefficient: r=0.942 Tickets Sold in 2014: About 1542.6 million tickets
Practice makes perfect
We are given a table for years and the number of movie tickets sold.
Movie Tickets Sold in U.S. by Year
Year
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Tickets Sold (millions)
1289
1311
1340
1339
1406
1421
1470
1415
1472
1470
To find the equation of the line of best fit, we have to perform a linear regression on our data points. Before we can do that, though, we first have to enter the values into lists. Push STAT and choose the EDIT menu. Choose the first option, Edit, and enter the values in the first two columns.
Next, we press STAT and choose CALC. In this menu, you will see all the different regressions that are available. The regression we want to perform is under the fourth option, LinReg(ax+b). By scrolling down to the fourth option and pressing ENTER twice, the calculator performs a linear regression.
By using the information in the calculator we will write the linear regression.
y=21.4x-41 557
Additionally, we see that the correlation coefficient r is about 0.942, which implies that our linear regression is a good fit. In order to predict the number of movie tickets sold in 2014 we will substitute x=2014 in the line of best fit and evaluate.
