EdX

Introductory Statistics : Basic Ideas and Instruments for Statistical Inference (edX)

Offered by Seoul National University, SNUx,
Introductory Statistics : Basic Ideas and Instruments for Statistical Inference (edX)

This course utilizes real-life applications of Statistics in an exploration of the Statistical Inferenceprocess. Statistical Inference is the process by which data is used to draw a conclusionoruncover ascientific truthabout a population from asample. This course aims to familiarize the student with several ideas and instruments for statistical inference. It covers fundamental concepts and properties of probability.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Specifically, youwill learn to work with sequences of successes and failures using the binomial formula. You will also learn how the law of averages can be used, as well as how to understand stochastic processes by applying box models. The normal approximation for probability histogram, which is an essential idea for statistical inference, will be discussed in depth in this course.

What you'll learn

  • Probability
  • The Binomial Formula
  • The Law of Averages
  • The Expected Value and Standard Error
  • The Normal Approximation for Probability Histograms

Syllabus

Week 1

  • Probability
  • Examples of Probability Calculation

Week 2

  • The Binomial Formula
  • The Law of Averages
  • The Expected Value and Standard Error

Week 3

  • The Normal Approximation for Probability Histograms
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Statistics and R (edX) EdX
HarvardX,Harvard University

Statistics and R (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation.

Self Paced
Self-Paced
Statistics Data Analysis Statistical Inference
Details
Probability and Statistics IV: Confidence Intervals and Hypothesis Tests (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics IV: Confidence Intervals and Hypothesis Tests (edX)

Statistics & Data Analysis

This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. Confidence intervals allow us to make probabilistic statements such as: “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug”?

Self Paced
Self-Paced
Statistics Probability Hypothesis
Details
Probability and Statistics I: A Gentle Introduction to Probability (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics I: A Gentle Introduction to Probability (edX)

Statistics & Data Analysis

This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems. In order to make the course completely self-contained (and to bring back long-lost memories), we’ll start off with Bootcamp lessons to review concepts from set theory and calculus.

Self Paced
Self-Paced
Calculus Statistics Analysis
Details
Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX) EdX
Seoul National University,SNUx

Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX)

Economics & Finance Statistics & Data Analysis

This course teaches basic statistical concepts and explores many compelling applications of statistical methods using real-life applications of Statistics. Why do we study statistics? The field of statistics provides professionals and scientists withconceptual foundations and useful techniques for evaluating ideas, testing theories, and - ultimately -uncovering the truth in any situation.

Self Paced
Self-Paced
Statistics Regression Data Analysis
Details
Data Science: R Basics (edX) EdX
HarvardX,Harvard University

Data Science: R Basics (edX)

Statistics & Data Analysis Data Science

Build a foundation in R and learn how to wrangle, analyze, and visualize data. This course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states.

Self Paced
Self-Paced
Probability Machine Learning Inference
Details
MathTrackX: Probability (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Probability (edX)

Sci: Mathematics

Understand probability and how it manifests in the world around us. This course introduces probability and how it manifests in the world around us. Beginning with discrete random variables, together with their uses in modelling random processes involving chance and variation, you will start to uncover the framework for statistical inference.

Self Paced
Self-Paced
Math Probability Mathematics
Details
Introducción a Ciencias de Datos y Estadística Básica para Negocios (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Introducción a Ciencias de Datos y Estadística Básica para Negocios (edX)

Statistics & Data Analysis

En este curso adquirirás los métodos estadísticos para la toma de decisiones en los negocios, así como herramientas tecnológicas para desarrollar habilidades cuantitativas. Áreas como el “big data” requieren un conocimiento muy claro de la estadística; en las áreas de negocios, la tecnología pone a nuestro alcance diversas aplicaciones que requieren una sólida formación en estadística para su correcto uso e interpretación.

Self Paced
Self-Paced
Business Statistics Decision Making
Details
Fundamentals of Statistics (edX) EdX
MIT,MITx

Fundamentals of Statistics (edX)

Statistics & Data Analysis

Develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing and prediction. Statistics is the science of turning data into insights and ultimately decisions. Behind recent advances in machine learning, data science and artificial intelligence are fundamental statistical principles. The purpose of this class is to develop and understand these core ideas on firm mathematical grounds starting from the construction of estimators and tests, as well as an analysis of their asymptotic performance.

Aug 26th 2026
13-24 Weeks
Statistics Linear Models Confidence Intervals
Details
R Data Science Capstone Project (edX) EdX
IBM

R Data Science Capstone Project (edX)

Statistics & Data Analysis

Apply various data analysis and visualization skills and techniques you have learned by taking on the role of a data scientist working with real-world data sets. In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R or IBM Data Analytics with Excel and R Professional Certificate Programs.

Self Paced
Self-Paced
Statistics Data Analysis Linear Regression
Details
MathTrackX: Statistics (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Statistics (edX)

Sci: Mathematics

Understand fundamental concepts relating to statistical inference and how they can be applied to solve real world problems. This course will build on probability and random variable knowledge gained from previous courses in the MathTrackX XSeries with the study of statistical inference, one of the most important parts of statistics.

Self Paced
Self-Paced
Math Statistics Statistical Inference
Details