Use the formula $L = 10 log_{10} (I/I_0)$, where $I_0 = 10^{-12} W/m^2$. Substitute the given intensity $I$ into the formula and calculate the value of $L$.

Use logarithmic regression on a calculator or software to find the logarithmic function that best fits the data. Identify the parameters of the model, such as the coefficients and constants.

Substitute $x = 0.0001$ into the model: $y = 10 log_{10}(0.0001)$. Calculate the value of $y$, which represents the predicted sound level in decibels.

Look for situations where changes in one variable result in proportional changes in another, especially when dealing with large ranges of values. Check if the data exhibits a logarithmic relationship.

The derivative of a logarithmic function represents the rate of change of the function. The graph shows that the rate of change decreases as $x$ increases.

The graph of $y = ln(x)$ is the reflection of the graph of $y = e^x$ over the line $y = x$, as they are inverse functions.

$L = 10 log_{10} (I/I_0)$ where $L$ is the sound level, $I$ is the sound intensity, and $I_0$ is the reference intensity.

$y = m log_b(x) + c$, where $y$ is the dependent variable, $x$ is the independent variable, $b$ is the base of the logarithm, and $m$ and $c$ are constants.

$L = 10 log_{10} (1.0/10^{-12}) = 120 ext{ dB}$

$L = 10 log_{10} (0.1/10^{-12}) = 110 ext{ dB}$

$L = 10 log_{10} (0.01/10^{-12}) = 100 ext{ dB}$

$L = 10 log_{10} (0.001/10^{-12}) = 90 ext{ dB}$