Independent Bernoulli trials are performed, with probability $1/2$ of success, until there has been at least one success. Find the PMF of the number of trials performed.
How is this different from the negative binomial?
Independent Bernoulli trials are performed, with probability $1/2$ of success, until there has been at least one success. Find the PMF of the number of trials performed.
How is this different from the negative binomial?
This is the geometric distribution, # of trials needed to get first success
$P(x=k) = (1-p)^{k-1}\cdot p$
The negative binomial distribution gives the # of trials needed to get k successes
So, as has been commented, the geometric distribution is a special case of the negative binomial distribution.
Note
Some count the # of failures for the negative binomial, but as you must be knowing, what is defined as "success" is just a matter of convenience.
First we need to observe that the range of $X$ is $\{2, 3, 4, \dots\}$. So for each integer $k \geq 2$, we get
$$ \{X = k\} \;=\; [S_1 \cap S_2 \cap S_3 ... \cap S_{k-1} \cap S^c_k] \;\cup\; [S^c_1 \cap S^c_2 \cap S^c_3 ... \cap S^c_{k-1} \cap S_k]. $$
So, we have,
$$
\mathbb{P}(X = k) \;=\; \mathbb{P}(S_1 \cap S_2 \cap S_3 ... \cap S_{k-1} \cap S^c_k) \;+\; \mathbb{P}(S^c_1 \cap S^c_2 \cap S^c_3 ... \cap S^c_{k-1} \cap S_k)
$$
$$= \; p^{k-1}(1-p) + (1-p)^{k-1}p.$$