An experiment is run. The mass of an object is recorded over time.
\begin{tabular}{|c|c|}
\hline Time (min) & Mass (g) \\
\hline 19 & 40 \\
\hline 28 & 34 \\
\hline 29 & 27 \\
\hline 40 & 26 \\
\hline 46 & 22 \\
\hline
\end{tabular}

Plot the points in the grid below.
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Draw:
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Using your calculator, run a linear regression to determine the equation of the line of best fit. Round to two decimal places, use $x$ for the variable.
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y=
\]

Step 1 ：An experiment is run. The mass of an object is recorded over time. The data is as follows: \n\n\begin{tabular}{|c|c|}\n\hline Time (min) & Mass (g) \\ \hline 19 & 40 \\ \hline 28 & 34 \\ \hline 29 & 27 \\ \hline 40 & 26 \\ \hline 46 & 22 \\ \hline\end{tabular}

Step 2 ：Plot the points in the grid below.

Step 3 ：Using your calculator, run a linear regression to determine the equation of the line of best fit. Round to two decimal places, use \(x\) for the variable.

Step 4 ：Create two lists, one for time and one for mass. Use these lists to perform a linear regression.

Step 5 ：Time = [19, 28, 29, 40, 46] and Mass = [40, 34, 27, 26, 22]

Step 6 ：The slope of the line of best fit is -0.62 and the intercept is 49.86.

Step 7 ：The equation of the line of best fit is \(y = -0.62x + 49.86\). This equation can be used to predict the mass of the object at any given time.

Step 8 ：Final Answer: The equation of the line of best fit is \(\boxed{y = -0.62x + 49.86}\).