liveBook · Manning

Scipy.stats.norm.cdf

scipy.stats.norm.cdf is a SciPy function that evaluates the cumulative distribution function of a normal distribution at specified values.

How 2 Manning books explain it

Statistics Every Programmer Needs

scipy.stats.norm.cdf is a SciPy function that evaluates the cumulative distribution function of a normal distribution at specified values.

How it is used
Computes cumulative normal probabilities for percentiles, intervals, and deadline-based project decisions.
How deep it goes
Explains standardization and cumulative-area subtraction with Python examples, but does not develop the normal-distribution derivation.
Examples
Demonstrates one-standard-deviation percentiles, the 1.0-to-1.5 interval, and a 30-week project deadline.
What you can do after
Apply it via SciPy to convert standardized values into cumulative probabilities and differences between probability bounds.

Read how Statistics Every Programmer Needs explains scipy.stats.norm.cdf →

Grokking Statistics

A SciPy function that returns the cumulative distribution function value for a normal distribution.

How it is used
Calculates normal-distribution probabilities below a value or between two values.
How deep it goes
Explains cumulative area, interprets results, and demonstrates subtraction, but does not derive the CDF internally.
Examples
Uses golden retriever weights, a 64-pound mean, a 3-pound standard deviation, and the 61-to-63-pound interval.
What you can do after
Apply it via SciPy to compute and interpret cumulative or interval probabilities for a normal distribution.

Read how Grokking Statistics explains scipy.stats.norm.cdf →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.