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Probability & Statistics courses

Probability and statistics courses explore mathematical concepts for analyzing random events and interpreting data through models and inference. Use tools such as Python, R, Excel and Google Sheets to apply your theoretical knowledge in statistics.

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Recommended for Probability & Statistics beginners

Build your Probability & Statistics skills with interactive courses, curated by real-world experts

course

Introduction to Statistics in R

मध्यवर्तीकौशल स्तर
4 hours
4.9K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Track

Statistician in R

52 hours
956
A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

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मूल्यांकन करें

Probability & Statistics पाठ्यक्रमों और ट्रैक को ब्राउज़ करें

course

ARIMA Models in R

बुनियादीकौशल स्तर
4 hours
346
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

course

Foundations of Inference in R

मध्यवर्तीकौशल स्तर
4 hours
343
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

course

Statistical Simulation in Python

मध्यवर्तीकौशल स्तर
4 hours
307
Learn to solve increasingly complex problems using simulations to generate and analyze data.

course

Experimental Design in R

मध्यवर्तीकौशल स्तर
4 hours
305
In this course youll learn about basic experimental design, a crucial part of any data analysis.

course

Generalized Linear Models in R

मध्यवर्तीकौशल स्तर
4 hours
293
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

course

Analyzing Survey Data in R

मध्यवर्तीकौशल स्तर
4 hours
270
Learn survey design using common design structures followed by visualizing and analyzing survey results.

course

Statistical Thinking in Python (Part 2)

मध्यवर्तीकौशल स्तर
4 hours
265
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

course

Foundations of Probability in Python

मध्यवर्तीकौशल स्तर
5 hours
261
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

course

Error and Uncertainty in Google Sheets

मध्यवर्तीकौशल स्तर
4 hours
254
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

course

Foundations of Inference in Python

विकसितकौशल स्तर
4 hours
252
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

course

Introduction to Network Analysis in Python

मध्यवर्तीकौशल स्तर
4 hours
238
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

course

Survival Analysis in R

मध्यवर्तीकौशल स्तर
4 hours
237
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

course

Advanced Probability: Uncertainty in Data

विकसितकौशल स्तर
2 hours
230
Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.

course

A/B Testing in R

मध्यवर्तीकौशल स्तर
4 hours
212
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

course

Survival Analysis in Python

विकसितकौशल स्तर
4 hours
209
Use survival analysis to work with time-to-event data and predict survival time.

course

Factor Analysis in R

विकसितकौशल स्तर
4 hours
204
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

course

Practicing Statistics Interview Questions in Python

विकसितकौशल स्तर
4 hours
178
Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

course

Network Analysis in R

मध्यवर्तीकौशल स्तर
4 hours
172
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

course

Inference for Numerical Data in R

विकसितकौशल स्तर
4 hours
167
In this course youll learn techniques for performing statistical inference on numerical data.

course

Case Studies in Statistical Thinking

मध्यवर्तीकौशल स्तर
4 hours
142
Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

course

Discrete Event Simulation in Python

विकसितकौशल स्तर
4 hours
135
Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

course

Practicing Statistics Interview Questions in R

विकसितकौशल स्तर
4 hours
126
In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

course

Introduction to Anomaly Detection in R

मध्यवर्तीकौशल स्तर
4 hours
122
Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.

course

Inference for Categorical Data in R

विकसितकौशल स्तर
4 hours
120
In this course youll learn how to leverage statistical techniques for working with categorical data.

Probability & Statistics पर संबंधित संसाधन

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How to Become a Statistician in 2026

Curious about how to become a statistician? Find out what a statistician does, what you need to get started, and what you can expect from this career.
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An Introduction to Statistical Machine Learning

Discover the powerful fusion of statistics and machine learning. Explore how statistical techniques underpin machine learning models, enabling data-driven decision-making.
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Determine if there is a significant difference between the means of the two groups using t.test() in R.
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Abid Ali Awan

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    Frequently asked questions

    How does probability and statistics related to data science?

    Probability and statistics are foundational to data science, offering the tools and frameworks necessary for analyzing data, making predictions, and deriving meaningful insights. They enable data scientists to understand patterns, assess uncertainties, and make informed decisions based on data analysis.

    Why is it important to develop knowledge in probability and statistics?

    Developing knowledge in probability and statistics is crucial for effectively interpreting data and making reliable predictions. This understanding forms the basis for designing experiments, analyzing results, and validating conclusions in various fields, ensuring decisions are data-driven and evidence-based.

    What careers can I pursue with knowledge in probability and statistics?

    With knowledge in probability and statistics, you can pursue a wide array of careers such as data scientist, market researcher, machine learning engineer, statistical analyst, and risk manager. These roles span various industries including finance, healthcare, technology, and government, where interpreting data and making evidence-based decisions are key.

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