The following data show the number of components (per square inch, in millions) being packed on a Pentium-type chip, for years 1994 to 2015. Let x be the number of years since 1994 (e.g., x = 0 for 1994, x = 3 for 1997, €¦, x = 21 for 2015) and let y be the number of components on a chip. The prediction equation when fitting an exponential regression model to these data equals yÌ‚ = 151.61 × 1.191^x.

a. What is the predicted number of components per square inch in 2015?
b. By how much does the predicted number of components increase per year over the time range that these data cover?
c. The correlation between the logarithm of the count and x equals 0.985, and the scatterplot with the log counts shows a linear trend. What does this suggest about whether the exponential regression model is appropriate for these data?

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Year Count Count Chip Chip Year 2008 2010 1794 3043 2482 Pentium 1994 1997 14 24 PentiumE PentiumII PentiumG 2011 2013 1999 2000 PentiumIII 48 PentiumG Pentium4 125 PentiumG 5645 2005 PentiumD 720 PentiumG 2015 5103 2007 971 PentiumE