-9 + 2 = 7
7 + 9 = 16
X = 16
<span>Linear regression is a method of finding the linear equation that comes closest to fitting a collection of data points.
</span>The better the choice of line, the closer the predicted values will be to the observed values.
The differences between the data pints (observed values) and the estimated (pedicted) regression line is called the <span>residue.
</span>Residue = Observed Value -<span> Predicted Value</span>
Answer:145.44 ounces
Step-by-step explanation: Formula
multiply the mass value by 16 which means multiply 9.09 by 16
Remember property of exponents

add exponents of same base
ok so
50,000 is 5 times 10^4
so
50000 times 10^15=
5 times 10^4 times 10^15=
5 times

=
5 times 10^19