scipystatsnormppf
The function `scipy.stats.norm.ppf` is a numerical method provided by the SciPy library in Python, specifically within the `scipy.stats` module, which computes the percent-point function (also known as the inverse of the cumulative distribution function, or CDF) for the normal distribution. The normal distribution, often referred to as the Gaussian distribution, is a continuous probability distribution characterized by its bell-shaped curve, defined by its mean (μ) and standard deviation (σ).
The `ppf` function, short for percentile point function, returns the value below which a given percentage of
The function signature is `scipy.stats.norm.ppf(q, loc=0.0, scale=1.0)`, where:
- `q` is the quantile (a value between 0 and 1) for which the inverse CDF is computed.
- `loc` is the mean (μ) of the distribution, defaulting to 0.0.
- `scale` is the standard deviation (σ) of the distribution, defaulting to 1.0.
The `ppf` function is particularly useful in scenarios where the exact inverse CDF cannot be expressed analytically,
For instance, in hypothesis testing, `ppf` helps determine the threshold values that separate the acceptance and