Summary  
This chapter demonstrates how to compute a confidence interval for a sample mean using a statistics library function by specifying the confidence level, mean (loc), and standard error (scale), and explains the concept of standard error of the mean.  

General domain of usage  
Statistical data analysis (inferential statistics)

## What Values Can We Estimate Using a Confidence Interval?

In this course, we will estimate mean values, but you can also estimate other statistics such as variances, mathematical expectations, and more.

Explore the function used to calculate confidence intervals.


```python
st.norm.interval(confidence=0.95, loc=np.mean(dist), scale=st.sem(dist))
```

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)

Which of the following statements about the `st.norm.interval()` function and standard error of the mean are correct?

Learn core statistical concepts used in data analysis with Python. The course covers descriptive statistics, including mean, median, mode, variance, and standard deviation, as well as sampling, probability distributions, the Central Limit Theorem, and outlier detection.

Calculating Confidence Interval with Python

What Values Can We Estimate Using a Confidence Interval?

What Is Standard Error of the Mean?