EdX

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

Offered by Seoul National University, SNUx,
Introductory Statistics : Analyzing Data Using Graphs and Statistics (edX)

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.

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

This course will familiarize you with data and basic statistical concepts, enabling you to analyze data using graphs and statistics. We'll start with types of data, controlled experiments,and observational study. You'll learn to use a histogram, a representation of the distribution of numerical data, to easily arrange data.
You will learn about basic concepts of statistics, such as average and standard deviation. Methods of using the normal approximation to solve a problem will be covered in this course. In addition, we'll discuss the correlation coefficient and the regression method in order to represent the relationship between two variables.

What you'll learn

  • Statistics and Data
  • The Histogram
  • The Average and the Standard Deviation
  • The Normal Approximation
  • Correlation
  • Regression
  • The Error for Regression
  • Regression Line

Syllabus

[Week 1]
Statistics and Data
The Histogram
[Week 2]
The Average and the Standard Deviation
The Normal Approximation
[Week 3]
Correlation
Regression
[Week 4]
The Error for Regression
Regression Line

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Advanced Statistical Inference and Modelling Using R (edX) EdX
University of Canterbury,UCx

Advanced Statistical Inference and Modelling Using R (edX)

Sci: Mathematics Statistics & Data Analysis

Extend your knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up. Advanced Statistical Inference and Modelling Using R is part two of the Statistical Analysis in R professional certificate. This course is directed at people who are already familiar with basic linear regression and fundamentals of statistical inference. It extends the knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up.

Self Paced
Self-Paced
Modeling Data Analysis Linear Regression
Details
Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

CS: Programming Data Science

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Programming Big Data Data Analysis
Details
Analytics for Decision Making (edX) EdX
Babson College

Analytics for Decision Making (edX)

Management & Leadership Statistics & Data Analysis

Discover the foundational concepts that support modern data science and learn to analyze various data types and quality to make smart business decisions. Want to know how to avoid bad decisions with data? Making good decisions with data can give you a distinct competitive advantage in business. This statistics and data analysis course will help you understand the fundamental concepts of sound statistical thinking that can be applied in surprisingly wide contexts, sometimes even before there is any data! Key concepts like understanding variation, perceiving relative risk of alternative decisions, and pinpointing sources of variation will be highlighted.

Self Paced
Self-Paced
Data Analysis Decision Making Analytics
Details
Case Studies in Functional Genomics (edX) EdX
HarvardX,Harvard University

Case Studies in Functional Genomics (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions.

Self Paced
Self-Paced
Data Analysis Biological Data Genomics
Details
Basics of Statistical Inference and Modelling Using R (edX) EdX
University of Canterbury,UCx

Basics of Statistical Inference and Modelling Using R (edX)

Sci: Mathematics Statistics & Data Analysis

Learn why a statistical method works, how to implement it using R and when to apply it and where to look if the particular statistical method is not applicable in the specific situation. Basics of Statistical Inference and Modelling Using R is part one of the Statistical Analysis in R professional certificate.

Self Paced
Self-Paced
Statistics Modeling Data Analysis
Details
Excel avanzado: importación y análisis de datos (edX) EdX
Universitat Politècnica de València,UPValenciaX

Excel avanzado: importación y análisis de datos (edX)

CS: Information & Technology Statistics & Data Analysis

Conoce técnicas y estrategias avanzadas para importar, consolidar y visualizar con Excel datos provenientes de cualquier fuente. En este curso de análisis e interpretación de datos te presentaremos técnicas avanzadas de importación de datos y estrategias diversas para consolidarlos y prepararlos una vez importados de forma que puedas extraer las conclusiones que necesitas (basadas en nuestra experiencia en el uso de Microsoft Excel y demostradas con casos reales).

Self Paced
Self-Paced
Excel Microsoft Big Data
Details
Data Science: Inference and Modeling (edX) EdX
HarvardX,Harvard University

Data Science: Inference and Modeling (edX)

Statistics & Data Analysis Data Science

Learn inference and modeling, two of the most widely used statistical tools in data analysis. Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting.

Self Paced
Self-Paced
Statistics Inference Modeling
Details
Visualizing Data with Python (edX) EdX
IBM

Visualizing Data with Python (edX)

Statistics & Data Analysis CS: Programming

Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. "A picture is worth a thousand words." We are all familiar with this expression. It especially applies when trying to explain the insights obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way.

Self Paced
Self-Paced
Python Maps Charts
Details
Excel for Everyone: Core Foundations (edX) EdX
The University of British Columbia,UBCx

Excel for Everyone: Core Foundations (edX)

Statistics & Data Analysis

Learn Excel fundamentals including data wrangling, spreadsheet management, and basic data analysis. This introductory Excel course will equip you with a strong foundational knowledge of Excel to organize, analyze and work with data. You will develop essential Excel skills, such as simple data wrangling and managing spreadsheets, along with a foundational understanding of business data analysis.

Self Paced
Self-Paced
Spreadsheets Excel Data Analysis
Details
Probability and Statistics II: Random Variables – Great Expectations to Bell Curves (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics II: Random Variables – Great Expectations to Bell Curves (edX)

Statistics & Data Analysis

This course discusses properties and applications of random variables. For instance, how many customers are likely to arrive in the next hour? What’s the probability that a lightbulb will last more than a year? When you’re done with this course, you’ll have enough firepower to undertake a wide variety of modeling and analysis problems; and you’ll be well-prepared for the upcoming Statistics courses.

Self Paced
Self-Paced
Statistics Probability Variance
Details
Statistical Inference and Modeling for High-throughput Experiments (edX) EdX
HarvardX,Harvard University

Statistical Inference and Modeling for High-throughput Experiments (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

A focus on the techniques commonly used to perform statistical inference on high throughput data. In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. We then introduce statistical modeling and how it is applied to high-throughput data. In particular, we will discuss parametric distributions, including binomial, exponential, and gamma, and describe maximum likelihood estimation.

Self Paced
Self-Paced
Statistics Modeling Statistical Inference
Details