I wanted to deeply understand what $PDF$ and $CDF$ meant. For a binomial distribution with $n$ trials and parameters $p$, we use the $PDF$ (for discrete case) to find $P(X = 3)$ where $X$ is a random variable representing the number of heads and there are $10$ trials.
For the continuous case, The $PDF$ is used to find $P[a\leq X\leq b] $ as $\int _{a}^{b}f_{X}(x)\,dx,$ where $f_{X}(x)$ is the PDF.
So I saw a problem, $X$ is a normally normally distributed variable with mean $μ$ = 30 and standard deviation $σ^2$ = 4. Find $P(30 < x < 35)$
I know how to use the $Z$-table, but why do we not find the answer using: $\int _{30}^{35}{\displaystyle {\frac {1}{\sqrt {2\pi \sigma ^{2}}}}e^{-{\frac {(x-\mu )^{2}}{2\sigma ^{2}}}}}\,dx$? Or do we almost always use the $PDF$ approach to solve such problems and I've just never encountered it because $Z$-table approach makes it a lot easier? Or does this have something to do with the fact that integrating this particular $PD$F for Normal Distribution is hard? I don't have an extremely deep background in mathematics so I don't know.
Also I apologize for usage of any wrong notations and symbols.
Well, have you ever tried finding the integral? Look at it. It is rather horrible, isn't it? It turns out that:
$${\displaystyle \int _{30}^{35}{\frac {1}{\sqrt {2\pi \sigma ^{2}}}}e^{-{\frac {(x-\mu )^{2}}{2\sigma ^{2}}}}}\,\mathsf dx =\dfrac 12\operatorname{erf}\left(\dfrac{5}{2\surd 2}\right) $$
But what the heck is this error function thing? Well, it is defined as: $$\operatorname{erf}(x)=\dfrac{1}{\surd\pi}\int_{-x}^x e^{-t^2}\operatorname d x = \dfrac{1}{2\surd\pi}\sum_{n=0}^{\infty}\dfrac{x}{2n+1}\prod_{k=1}^{n}\dfrac{-z^{-2}}{k}$$
What is the closed form of this thing? Well... it doesn't appear to have one.
So, the cummulative probability distribution function for a normal distribution is simply not expressable in terms of elementary functions. It has to be evaluated through numerical means.
So we use precompiled tables (or software) to find the answer when we need it.