## Introduction to Statistics in Python

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

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69 results ## Introduction to Statistics in Python

## Introduction to Statistics

## Introduction to Statistics in R

## Introduction to Regression in R

## Hypothesis Testing in Python

## Sampling in Python

## Hypothesis Testing in R

## Introduction to Regression with statsmodels in Python

## Intermediate Regression in R

## Sampling in R

## Time Series Analysis in Python

## Foundations of Inference in R

## Statistical Thinking in Python (Part 1)

## Foundations of Probability in R

## Fundamentals of Bayesian Data Analysis in R

## Customer Analytics and A/B Testing in Python

## Statistical Thinking in Python (Part 2)

## Time Series Analysis in R

## Modeling with Data in the Tidyverse

## Hierarchical and Mixed Effects Models in R

## Introduction to Statistics in Spreadsheets

## Experimental Design in R

## Introduction to Network Analysis in Python

## A/B Testing in Python

## Foundations of Probability in Python

## Generalized Linear Models in R

## Analyzing Survey Data in R

## Linear Algebra for Data Science in R

## Forecasting in R

## Intermediate Regression with statsmodels in Python

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

4 hoursProbability & StatisticsMaggie Matsuicourses

Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

4 hoursProbability & StatisticsGeorge Boormancourses

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

4 hoursProbability & StatisticsMaggie Matsuicourses

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

4 hoursProbability & StatisticsRichie Cottoncourses

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

4 hoursProbability & StatisticsJames Chapmancourses

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

4 hoursProbability & StatisticsJames Chapmancourses

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

4 hoursProbability & StatisticsRichie Cottoncourses

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

4 hoursProbability & StatisticsMaarten Van den Broeckcourses

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hoursProbability & StatisticsRichie Cottoncourses

Master sampling to get more accurate statistics with less data.

4 hoursProbability & StatisticsRichie Cottoncourses

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

4 hoursProbability & StatisticsRob Reidercourses

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

4 hoursProbability & StatisticsJo Hardincourses

Build the foundation you need to think statistically and to speak the language of your data.

3 hoursProbability & StatisticsJustin Boiscourses

In this course, you'll learn about the concepts of random variables, distributions, and conditioning.

4 hoursProbability & StatisticsDavid Robinsoncourses

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

4 hoursProbability & StatisticsRasmus Bååthcourses

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

4 hoursProbability & StatisticsRyan Grossmancourses

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

4 hoursProbability & StatisticsJustin Boiscourses

Learn the core techniques necessary to extract meaningful insights from time series data.

4 hoursProbability & StatisticsDavid S. Mattesoncourses

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

4 hoursProbability & StatisticsAlbert Y. Kimcourses

In this course you will learn to fit hierarchical models with random effects.

4 hoursProbability & StatisticsRichard Ericksoncourses

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

4 hoursProbability & StatisticsTed Kwartlercourses

In this course you'll learn about basic experimental design, a crucial part of any data analysis.

4 hoursProbability & StatisticsJoanne Xiongcourses

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

4 hoursProbability & StatisticsEric Macourses

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

4 hoursProbability & StatisticsMoe Lotfy, PhDcourses

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

5 hoursProbability & StatisticsAlexander A. Ramírez M.courses

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

4 hoursProbability & StatisticsRichard Ericksoncourses

Learn survey design using common design structures followed by visualizing and analyzing survey results.

4 hoursProbability & StatisticsKelly McConvillecourses

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

4 hoursProbability & StatisticsEric Eagercourses

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

5 hoursProbability & StatisticsRob J. Hyndmancourses

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hoursProbability & StatisticsMaarten Van den Broeckcourses