Conteúdo do Curso
Learning Statistics with Python
Learning Statistics with Python
Calculating Confidence Interval with Python
What Values Can We Estimate Using a Confidence Interval?
In this course, we will estimate mean values, but you can estimate other statistics such as variances, mathematical expectations, and more.
Now, let's delve into the function for calculating confidence intervals.
The st.norm.interval()
function is used to compute a confidence interval with the following parameters:
- The
confidence
parameter represents the confidence level; - The
loc
parameter signifies the mean value of the distribution; - The
scale
is the standard error of the mean.
What Is Standard Error of the Mean?
The standard error of the mean, often called standard error, measures how likely the population mean is to deviate from a sample mean.
Try to change the confidence
parameter and observe the changes.
# Importing libraries import scipy.stats as st import numpy as np # Creating random normal distribution dist = st.norm.rvs(size=1000, loc=50, scale=2) # Finding confidence interval confidence = st.norm.interval(confidence=0.95, loc=np.mean(dist), scale=st.sem(dist)) print(confidence)
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