The amount of methane emissions, in millions of metric tons, from 2002 to 2008 is shown.

A 2-column table with 7 rows. The first column is labeled year with entries 2002, 2003, 2004, 2005, 2006, 2007, 2008. The second column is labeled methane (millions of metric tons) with entries 673.3, 660.6, 661.6, 669.2, 678.5, 690.9, 724.2.
Find a regression model that best models the data.

The function that best models the data is .

Use the model to complete the statements.

The amount of methane emissions in 2000 was about million metric tons.

The amount of methane emissions in the years immediately following 2008 would most likely.

The amount of methane emissions, in millions of metric tons, from 2002 to 2008 is shown. So, the answer is 1) Quadratic 2) 711 metric tons and 3) Most Likely to Increase.

What is the fitting of the curve for a data plot?

When the data shows some trend, either linear (making a line), or non-linear (a predictable curve), we fit a mathematical curve on that data set, as a representative of the pattern in that data set, to predict the output based on the inputs.

A 2-column table with 7 rows.

The first column is labeled year with entries 2002, 2003, 2004, 2005, 2006, 2007, and 2008.

The second column is labeled methane (millions of metric tons) with entries 673.3, 660.6, 661.6, 669.2, 678.5, 690.9, and 724.2.

1) A regression model that best models the data would be the Quadratic function.

2) The amount of methane emissions in 2000 was about million metric tons.

It would be 711 metric tons

3) The amount of methane emissions in the years immediately following 2008 would most likely to Increase.

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