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Course

Introduction to Statistics in Python

Intermediate

4.7+

Updated 03/2025

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

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PythonProbability & Statistics4 hours15 videos54 Exercises4,250 XP138,447Statement of Accomplishment

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Course Description

Statistics is the study of how to collect, analyze, and draw conclusions from data. It’s a hugely valuable tool that you can use to bring the future into focus and infer the answer to tons of questions. For example, what is the likelihood of someone purchasing your product, how many calls will your support team receive, and how many jeans sizes should you manufacture to fit 95% of the population? In this course, you'll discover how to answer questions like these as you grow your statistical skills and learn how to calculate averages, use scatterplots to show the relationship between numeric values, and calculate correlation. You'll also tackle probability, the backbone of statistical reasoning, and learn how to use Python to conduct a well-designed study to draw your own conclusions from data.

Prerequisites

Data Manipulation with pandas

1

Summary Statistics

What is statistics?

Descriptive and inferential statistics

Data type classification

Measures of center

Mean and median

Mean vs. median

Measures of spread

Variance and standard deviation

Quartiles, quantiles, and quintiles

Finding outliers using IQR

2

Random Numbers and Probability

What are the chances?

With or without replacement?

Calculating probabilities

Sampling deals

Discrete distributions

Creating a probability distribution

Identifying distributions

Expected value vs. sample mean

Continuous distributions

Which distribution?

Data back-ups

Simulating wait times

The binomial distribution

Simulating sales deals

Calculating binomial probabilities

How many sales will be won?

3

More Distributions and the Central Limit Theorem

The normal distribution

Distribution of Amir's sales

Probabilities from the normal distribution

Simulating sales under new market conditions

Which market is better?

The central limit theorem

Visualizing sampling distributions

The CLT in action

The mean of means

The Poisson distribution

Identifying lambda

Tracking lead responses

More probability distributions

Distribution dragging and dropping

Modeling time between leads

The t-distribution

4

Correlation and Experimental Design

Correlation

Guess the correlation

Relationships between variables

Correlation caveats

What can't correlation measure?

Transforming variables

Does sugar improve happiness?

Confounders

Design of experiments

Study types

Longitudinal vs. cross-sectional studies

Congratulations!

Introduction to Statistics in Python

Course
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Included withPremium or Teams

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*4.7

from 1,381 reviews

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Most recent
Top reviews

Nikolay

about 2 hours

Cole

about 3 hours

Nguyễn

about 3 hours

Elier

about 4 hours

Pretty good overall to get an introduction about foundations of statistics

Jan-Ola

about 4 hours

A very enjoyable course that was clear, easy to follow, and covered the most important fundamentals of statistics.

Andras

about 2 hours

Nikolay

Cole

Nguyễn

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