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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

MellanliggandeFärdighetsnivå
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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course

ARIMA Models in R

GrundläggandeFärdighetsnivå
4 hours
337
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

course

Foundations of Inference in R

MellanliggandeFärdighetsnivå
4 hours
329
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

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Statistical Simulation in Python

MellanliggandeFärdighetsnivå
4 hours
311
Learn to solve increasingly complex problems using simulations to generate and analyze data.

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Experimental Design in R

MellanliggandeFärdighetsnivå
4 hours
301
In this course youll learn about basic experimental design, a crucial part of any data analysis.

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Generalized Linear Models in R

MellanliggandeFärdighetsnivå
4 hours
291
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

course

Analyzing Survey Data in R

MellanliggandeFärdighetsnivå
4 hours
264
Learn survey design using common design structures followed by visualizing and analyzing survey results.

course

Foundations of Probability in Python

MellanliggandeFärdighetsnivå
5 hours
260
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

course

Foundations of Inference in Python

AvanceradFärdighetsnivå
4 hours
256
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

course

Error and Uncertainty in Google Sheets

MellanliggandeFärdighetsnivå
4 hours
256
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

course

Survival Analysis in R

MellanliggandeFärdighetsnivå
4 hours
235
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

AvanceradFärdighetsnivå
2 hours
232
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

MellanliggandeFärdighetsnivå
4 hours
213
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

AvanceradFärdighetsnivå
4 hours
208
Use survival analysis to work with time-to-event data and predict survival time.

course

Factor Analysis in R

AvanceradFärdighetsnivå
4 hours
201
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

course

Network Analysis in R

MellanliggandeFärdighetsnivå
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

AvanceradFärdighetsnivå
4 hours
162
In this course youll learn techniques for performing statistical inference on numerical data.

course

Case Studies in Statistical Thinking

MellanliggandeFärdighetsnivå
4 hours
141
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

AvanceradFärdighetsnivå
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

AvanceradFärdighetsnivå
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

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

course

Inference for Categorical Data in R

AvanceradFärdighetsnivå
4 hours
118
In this course youll learn how to leverage statistical techniques for working with categorical data.

Relaterade resurser på Probability & Statistics

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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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