Q = (1/r)√(l/c)
To calculate the number of electrons required to produce a charge of 230 microcoulombs, you can use the formula Q = N * e, where Q is the charge, N is the number of electrons, and e is the elementary charge (1.6 x 10^-19 C). Rearranging the formula, N = Q / e will give the number of electrons. Plugging in the values, N = 230 * 10^-6 / (1.6 x 10^-19) ≈ 1.44 x 10^15 electrons.
To calculate the energy absorbed by the water, you can use the equation Q = mcΔT, where Q is the energy absorbed, m is the mass of water (5kg), c is the specific heat capacity of water (4186 J/kg°C), and ΔT is the change in temperature (65°C - 30°C). Plugging in the values gives Q = 5kg * 4186 J/kg°C * (65°C - 30°C). Calculate this to find the energy absorbed in joules.
Q = mc(dT) where dT = the change in temperature of the substance. Knowing that the specific heat of water (c) is 4.186 J/g C and that m = 5g we can find the solution. Q = (5g)(4.186 J/g C)(150-105)C Q = 941.85 J
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To calculate the enthalpy change or heat energy of a phase change, use the formula q=m(heat of (fusion, vaporization, etc...)). Make sure to use the formula q=mc(delta T) to calculate the heat energy for the temperature changes in between phase changes. Add up all of the q values and you have your enthalpy change.
Important Formula: Sin(q) = Opposite / Hypotenuse Cos(q) = Adjacent / Hypotenuse Tan(q) = Opposite / AdjacentSelect what (angle / sides) you want to calculate, then enter the values in the respective rows and click calculate. If you want to calculate hypotenuse enter the values for other sides and angle.
Ifp < q and q < r, what is the relationship between the values p and r? ________________p
p = q
The truth values.
To calculate the charge on each capacitor in the circuit, you can use the formula Q CV, where Q is the charge, C is the capacitance of the capacitor, and V is the voltage across the capacitor. Simply plug in the values for capacitance and voltage for each capacitor in the circuit to find the charge on each one.
The singular values of an orthogonal matrix are all equal to 1. This is because an orthogonal matrix ( Q ) satisfies the property ( Q^T Q = I ), where ( I ) is the identity matrix. Consequently, the singular value decomposition of ( Q ) reveals that the singular values, which are the square roots of the eigenvalues of ( Q^T Q ), are all 1. Thus, for an orthogonal matrix, the singular values indicate that the matrix preserves lengths and angles in Euclidean space.
To find the value of q in chemistry, one can use the formula q m c T, where q represents the heat energy, m is the mass of the substance, c is the specific heat capacity, and T is the change in temperature. By plugging in the known values for mass, specific heat capacity, and temperature change, one can calculate the value of q.
Choose some values for x. Then calculate the corresponding values of y using the formula. Put these values in a table.Choose some values for x. Then calculate the corresponding values of y using the formula. Put these values in a table.Choose some values for x. Then calculate the corresponding values of y using the formula. Put these values in a table.Choose some values for x. Then calculate the corresponding values of y using the formula. Put these values in a table.
p=q
The KLD is more or less a measure of how much information is lost when an approximation is used to replace an actual probability distribution. How you calculate it depends on whether you are considering discrete or continuous values for the distribution. If you have discrete values, KLD = Σ P(i) log [P(i)/Q(i)] (summing over the values of i) where P(i) is the "true" distribution and Q(i) a corresponding approximation. If you have a continuous function for the probability, i.e. the variable can assume any value over a certain range (usually with different probability density for different values since uniform probability is a pretty boring problem) KLD = ∫ p(x)log[p(x)/q(x)] dx (integrated from -∞ to +∞) where p(x) is the true function of the probability - the "density" of P, and q(x) is the approximated function of the probability - the "density" of Q. Note that these formulas only hold for a single variable. More complex formulas are required to calculate the KLD for multi-variable distributions.
To calculate the enclosed q value, use the formula q (m1 m2) / r, where m1 and m2 are the masses of the two objects and r is the distance between them.
p/q form of the number is 0.3 is: (A) (B)