Calculate posterior probability with given condition I am new to the world of Bayesian data analysis and I am trying to calculate the posterior probability with a given condition. I know how to calculate the posterior probability, but I am not sure how to do this when having a given condition. Suppose we have two globes: Earth and Mars. The Earth globe is 30% covered with land. The Mars globe covers 100% of the land. Suppose that the tossed observation was a globe with "land". Furthermore each globe was equally likely to be tossed. So I was wondering how can we calculate the posterior probability that the globe was Earth conditional seeing "land"?
I know that this could be written to this for posterior probability:
$$
P(Earth|land)=\frac{P(Earth)*P(land|Earth)}{P(land)}
$$
Then we know the following:
$$
P(Earth) = 0.5
$$
$$
P(land|Earth) = 0.7
$$
But how can we calculate the given condition $P(land)$ to determine the posterior probability?

By the law of total probability
$$
P(land) = P(land|Earth) P(Earth) + P(land|Mars) P(Mars)
$$
