The data in the table below represent the U.S. online advertising revenues for the years 2005–2016. 

(a) Using a graphing utility, draw a scatter plot of the data using 0 for 2005, 1 for 2006, and so on as the independent variable, and online advertising revenue as the dependent variable. 

(b) Based on the scatter plot drawn in part (a), decide what model (linear, quadratic, cubic, exponential, logarithmic, or logistic) that you think best describes the relation between year and revenue. 

(c) Using a graphing utitlity, find the model of best fit. 

(d) Using a graphing utility, graph the function found in part (c) on the scatter plot drawn in part (a). 

(e) Use your model to predict the online advertising revenue in 2021.

Transcribed Image Text:

Year 2005 (x = 0) 2006 (x = 1) 2007 (x = 2) 2008 (x = 3) 2009 (x = 4) 2010 (x = 5) 2011 (x = 6) 2012 (x = 7) 2013 (x = 8) 2014 (x = 9) 2015 (x = 10) 2016 (x = 11) U.S. Online Advertising Revenue ($ billions) 12.5 16.9 21.2 23.4 22.7 26.0 31.7 36.6 42.8 49.5 59.6 72.5