Pearson Algebra 2 Common Core, 2011
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Pearson Algebra 2 Common Core, 2011 View details
5. Using Linear Models
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Exercise 12 Page 96

Practice makes perfect
To find the line of best fit for the given data, we need to perform a linear regression. Starting by pushing STAT and choosing Edit, then enter the data into two lists. Production depends on time, so time is the independent variable and production is the dependent variable. Let year 2000 be x=0.

Next, push STAT and scroll right to the second option, CALC. In this menu, you can see all available regressions that the calculator can perform.

The regression we want is the fourth option, LinReg ax+b. By scrolling down to this choice and pushing ENTER twice, the calculator performs a linear regression and gives us the following output.

We will round the constant and the coefficient of x to two decimals, which gives us the following line of best fit. y=2053.16x+39 758.67

By substituting x=25 into the function we found in Part A, we can predict how many metric tons of pork will be produced 25 years after 2000, which is 2025.

y=2053.16x+39 758.67
y=2053.16( 25)+39 758.67
â–¼
Simplify right-hand side
y=51 329+39 758.67
y=91 087.67
y≈ 91 088

In 2025 the number of metric tons of pork produced will be about 91 088.

By setting y=100 000 we can solve for the number of years x, when the production reaches this point.

y=2053.16x+39758.67
100 000=2053.16x+39 758.67
â–¼
Solve for x
60 241.33=2053.16x
2053.16x=60 241.33
x=29.34078...
x≈ 29.3

In about 2029 the production will reach 100 000 metric tons.