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10 Best Online Probability & Statistics Courses and Tutorials of 2020

Probability & Statistics Courses

It is incredibly difficult to meet the requirements for students with so many Probability & Statistics courses. Learners often ask if each scenario has a course in Probability & Statistics. The answer is YES. Below you can find popular courses. Registration for the correct course is an important element in your career development. In this article, experts selected the best courses in Probability & Statistics in 2020.

Highlighting the best-known courses in all categories is the main objective.

Based on your preferences, select one that best suits your needs. But let us look at the best courses on the market for Probability & Statistics.

1. Statistics Certification with R from Duke University (Coursera)

Duration: 7 months

Rating : 4.7 out of 5 

Demystify R data, compile analytical reports, learn Bayesian statistical inference and model in this Duke University program. You will also learn to report statistical results, review data-based statements, evaluate decisions based on data and view data with R. The course is created and taught by the Associate Practice Professor, Mine Çetinkaya-Rundel, David Banks, Professor of Practice, Colin Rundel, Assistant Professor of Practice and Professor, Merlise A Clyde. When you want to study probability and statistics with R, this is an excellent alternative.

Key Highlights:

  • Statistics inferential
  • Modelling and linear regression
  • Probability and data introduction
  • R Capstone Project Statistics
  • Statistics of Bayesia

You can Sign up Here

2. Statistics and Data Science Micromaster Certification by MIT (edX)

Duration: 2 to 16 weeks per course, 10 to 14 hours per week, per course

Rating : 4.6 out of 5

This MicroMaster Program provides four online courses that will direct you to know the basic skills needed to understand the techniques and resources used in data science and learn from machine learning and data analytics. Beginning with the fundamental principles of probability and statistics, prior to actually moving on to data analytics and learning machine algorithms. The calculus at college level, mathematical reasoning and python programming skills are advisable to make the most of this certification. You are eligible to submit to specific data science profiles at the end of the program.

Key Highlights:

  • Teachers provide information and guidance on best practices for designing and applying algorithms using tools.
  • Enhance your data science, statistics and machine learning foundations through the five courses.
  • Build machine learning algorithms to acquire meaning and relevant information on unstructured data.
  • Learn how to analyze Big Data and make data-driven predictions using statistical inference and probabilistic analysis to derive practical decisions.
  • After completion of this certification, various job titles could well be applied, such as data scientists, data analysts, and system analysts to name just a few.
  • Research on common unattended learning methodologies such as clustering and supervised methods such as deep neural networks.

You can Sign up Here 

3. Methods and Statistics Course Online by University of Amsterdam (Coursera)

Duration: 9 months, 6 hours per week

Rating : 4.7 out of 5

You will learn to recognize and ask thoughtful questions, evaluate data sets, and interpret findings correctly in order to take rational and evidence-based actions in this online statistics training course. The lessons discuss the research methods, design and statistical analysis for social science-based research. In addition, the final project will allow you to apply your acquired knowledge in lessons to creating your own questions, gathering data, analysis and interpreting using statistical methods. When the certification is complete, you are confident that you will identify more complex research problems and seek answers.

Key Highlight

  • In qualitative research, learn about data collection, description, analysis and interpretation.
  • Since this is a beginner level curriculum there is no clear criterion for registration.
  • Discover the core values of behavioural and social science scientific methods.
  • Learn skills and perform tests required with the software applied to the courses.
  • Discuss mathematical principles so that you can use them to solve different problems.
  • Perform all graded tasks and evaluations in order to obtain the final badge.
  • Work with fellow students on the Capstone Project and formulate a hypothesis of research and carry out research and analysis.

You can Sign up Here

4. Data Science Course from John Hopkins University (Coursera)

Rating : 4.5 out of 5

There is a detailed course covering all different aspects of data science. The statistics part of this program helps you learn the statistical conclusions of the data drawing process. It covers all broad theories (frequentists, bayesians, probability) to infer. This is developed and taught by Biostatistics Professor Roger D. Peng; Brian Caffo, PhD Professor, Biostatistics, and Jeff Leek, PhD Associate Professor.

Key Highlights:

  • Data collection and cleaning
  • The toolbox of the data scientist
  • Review of exploratory data
  • Programmatization
  • Inference on statistics
  • Research reproducible
  • Learning Practical Machine
  • Models of Regression
  • Capstone Data Science Project
  • Product Data Development

You can Sign up Here

5. Bayesian Statistics Certification Course Part 1: From Concept to Data Analysis

Duration: 10 Hours

Rating : 4.5 out of 5

This program includes the Bayesian approach to statistics, beginning with the probability concept and moving towards data analysis. It is an intermediate specialization for individuals with basic Statistics knowledge and is taught by Herbert Lee, Professor of Applied Mathematics and Statistics.

Courses Covered:

  • Probability and Bayes’ Theorem
  • Statistical Inference
  • Priors and Models for Discrete Data
  • Models for Continuous Data

You can Sign up Here

6. Business Statistics Certification from Rice University (Coursera)

Duration: 5 months, 4 hours per week

Rating : 4.7 out of 5

Courses Covered:

  • Introduction to Data Analysis Using Excel
  • Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
  • Business Applications of Hypothesis Testing and Confidence Interval Estimation
  • Linear Regression for Business Statistics
  • Business Statistics and Analysis Capstone Project

You can Sign up Here

7. Workshop in Probability and Statistics Course Online (Udemy)

Duration: 30 Hours

Rating : 4.4 out of 5

George Ingersoll is the Associate Dean at the UCLA Anderson School of Management for Executive MBA Programms. This workshop has been developed to teach you probability, sampling, regression and decision analysis. This statistical tutorial is ideal for beginners and intermediate level people.

Courses Covered:

  • Joint and Conditional Probability
  • Bayes’ Rule & Random Variables
  • Probability Distributions
  • The Normal Distribution
  • Joint Random Variables
  • Hypothesis Testing
  • Simple Linear Regression
  • Multiple Regression

You can Sign up Here

8. Bayesian Statistics Certification Course Part 2: Techniques and Models

Duration: 30 Hours

Rating : 4.8 out of 5

The second course in the series is based on the first part and lets you deepen the area. It involves more general models and programming techniques. You can know MCMC processes, R and JAGS programming language. The lesson is a combination of abstract and practical knowledge and a project follows the course bit to help you better understand.

Course Covered:

  • Statistical modelling and Monte Carlo estimation
  • Markov chain Monte Carlo (MCMC)
  • Common statistical models
  • Count data and hierarchical modelling.
  • Capstone Project

You can Sign up Here

9. Inferring Causal Effects from Observational Data by University of Pennsylvania

Duration: 5 weeks, 3 to 5 hours per week

Rating: 4.7 out of 5

This tutorial will give you how to identify the causal effects, the assumptions about your data and models, and the techniques to apply and interpret some common statistical methods. You will also have the opportunity to use these methods to explain R results. Ultimately, this curriculum shows the significance of the topics discussed in other fields of research.

Key Highlights:

  • Explain the difference between association and causation, and express casual graph assumptions.
  • Identifying causal effects using potential results.
  • For each type of statistical method, it is important to consider casual assumptions.
  • Investigate and introduce many forms of causal inference procedures such as matching, instrumental variables, inverse treatment weighting probability.
  • Complete all the evaluations, tests and practical lessons to obtain a certificate of completion.
  • The curriculum is divided into different parts and taught by qualified experts.

You can Sign up Here

10. Online Statistics Course for Business Analytics A-Z™ (Udemy)

Duration: 30 Hours

Rating : 4.4 out of 5

Kirill Eremenko is an experienced data science teacher! So far, he has taught over 400,000 students and his students have an average ranking of 4.5! In this tutorial, he shows you the key stats required for a career in data science. He will help you master statistical significance, confidence intervals and a lot more.

Courses Covered:

  • Normal Distribution
  • Standard Deviations
  • Sampling Distribution
  • Central Limit Theorem
  • Hypothesis Testing for Means and Proportions
  • Z-Score and Z-Tables
  • t-Score and t-Tables

You can Sign up Here

11. Statistics for Data Science and Business Analysis (Udemy)

Duration: 5 hours

Rating : 4.5 out of 5

In this business training tailor, you learn about descriptive and inferential statistics, hypothesis testing, regression analysis and more. Know how to track various data forms, quantify core trend quantities, asymmetry and uncertainty.

Courses Covered:

  • Fundamentals of descriptive statistics
  • Measures of central tendency, asymmetry, and variability
  • Estimators and estimates
  • Confidence intervals: advanced topics
  • inferential statistics
  • Hypothesis testing
  • Hypothesis testing
  • Practical example: hypothesis testing
  • The fundamentals of regression

You can Sign up Here

12. Introduction to Statistics with NumPy (Codecademy)

Duration: 5 hours

Rating: 4.6 out of 5

It is another addition to Codecademy Statistics courses that will expose you to NumPy – the popular Python library used to calculate can descriptive statistics without writing scratch functions. In this course, the professor will not only teach you about NumPy, but will also direct you to a Python module for numerical operations on large data volumes. Besides this, you can hear about the fundamentals of statistical distributions used to classify datasets. You may also get a certification from the Codecademy after completing the course.

Key Highlights:

  • Learn how to build the basic NumPy data form, arrays, and how to add, remove and pick calculations;
  • An exciting NumPy course for statistical management and calculations
  • Get help and guidance from instructors with tests and exercises that will help you better learn
  • Understand descriptive statistical measurements such as sources, media and ranges
  • At the end of the course, create portfolio projects to demonstrate and analyze your skills
  • Explore and create histograms to visualize large numeric data volumes

You can Sign up Here

13. Statistics Course with R – Beginner Level

Duration: 5 hours

Rating : 4.4 out of 5

Courses Covered:

  • Data Manipulation in R
  • Descriptive Statistics
  • Creating Frequency Tables and Cross Tables
  • Building Charts
  • Checking Assumptions
  • Performing Univariate Analyses

You can Sign up Here

Wrapping Up

This is the list of the 13 Best Online Probability & Statistics Courses and Tutorials of 2020. They are popular and loved by many experienced Probability & Statistics Courses learners. You will find between these courses what you need to learn in order to continue your Probability & Statistics Courses learning journey.

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