Step 1: Recall Earth's equatorial radius. The Earth's equatorial radius is approximately: \[ 6378 \, \text{km} \]
Step 2: Compare with given planets. - Mercury: \(\sim 2440 \, \text{km}\) → much smaller. - Venus: \(\sim 6052 \, \text{km}\) → very close to Earth. - Mars: \(\sim 3390 \, \text{km}\) → smaller. - Neptune: \(\sim 24,622 \, \text{km}\) → much larger.
Step 3: Closest match. Among these, Venus has an equatorial radius closest to Earth.
Final Answer: \[ \boxed{\text{Venus}} \]
While doing Bayesian inference, consider estimating the posterior distribution of the model parameter (m), given data (d). Assume that Prior and Likelihood are proportional to Gaussian functions given by \[ {Prior} \propto \exp(-0.5(m - 1)^2) \] \[ {Likelihood} \propto \exp(-0.5(m - 3)^2) \] 
The mean of the posterior distribution is (Answer in integer)
Consider a medium of uniform resistivity with a pair of source and sink electrodes separated by a distance \( L \), as shown in the figure. The fraction of the input current \( (I) \) that flows horizontally \( (I_x) \) across the median plane between depths \( z_1 = \frac{L}{2} \) and \( z_2 = \frac{L\sqrt{3}}{2} \), is given by \( \frac{I_x}{I} = \frac{L}{\pi} \int_{z_1}^{z_2} \frac{dz}{(L^2/4 + z^2)} \). The value of \( \frac{I_x}{I} \) is equal to 