Answer:
18,850 Hz
Explanation:
We need to figure out the wavelength of the sound wave.
Thus,
Wavelength = 1000 * Lowest Amplitude Wave
Wavelength = 1000 * 2.0 * 10^(-5)
Wavelength = 0.02
Or,
Now, we need the frequency of this wave. It goes by the formula:
Where
f is the frequency in Hz
v is the speed of sound in air (to be 377 m/s)
is the wavelength (we found to be 0.02)
Substituting, we find the frequency:
The wave has frequency of 18,850 Hz
Answer:
The electric potential (voltage) 
produced by a point charge 
, at any point in space, is given by the following equation:
Where:
is the Coulomb's constant
is the distance
The result is a scalar quantity, is defined as the electric potential energy per unit of charge and determines the electric influence exerted by the charge on that point of space.
Answer:
(D) 4
Explanation:
The percentage error in each of the contributors to the calculation is 1%. The maximum error in the calculation is approximately the sum of the errors of each contributor, multiplied by the number of times it is a factor in the calculation.
density = mass/volume
density = mass/(π(radius^2)(length))
So, mass and length are each a factor once, and radius is a factor twice. Then the total percentage error is approximately 1% +1% +2×1% = 4%.
_____
If you look at the maximum and minimum density, you find they are ...
{0.0611718, 0.0662668} g/(mm²·cm)
The ratio of the maximum value to the mean of these values is about 1.03998. So, the maximum is 3.998% higher than the "nominal" density.
The error is about 4%.
_____
<em>Additional comment</em>
If you work through the details of the math, you will see that the above-described sum of error percentages is <em>just an approximation</em>. If you need a more exact error estimate, it is best to work with the ranges of the numbers involved, and/or their distributions.
Using numbers with uniformly distributed errors will give different results than with normally distributed errors. When such distributions are involved, you need to carefully define what you mean by a maximum error. (By definition, normal distributions extend to infinity in both directions.) While the central limit theorem tends to apply, the actual shape of the error distribution may not be precisely normal.
