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Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also... more
Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective.... more
This course describes Bayesian statistics, in which one\'s inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes\' rule to transform prior... more
This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces... more
What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a... more
Identify interesting questions, analyze data sets, and correctly interpret results to make solid, evidence-based decisions. This Specialization covers research methods, design and statistical... more
Welcome! Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you... more
Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the... more
We have all heard the phrase \"correlation does not equal causation.\" What, then, does equal causation? This course aims to answer that question and more! Over a period of 5 weeks, you will learn... more
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning... more
This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach... more
This course offers a rigorous mathematical survey of causal inference at the Master\'s level. Inferences about causation are of great importance in science, medicine, policy, and business. This... more
A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or... more
This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate... more
This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes... more
The lectures of this course are based on the first 11 chapters of Prof. Raymond Yeung\'s textbook entitled Information Theory and Network Coding (Springer 2008). This book and its predecessor, A... more
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.Created by: Johns Hopkins UniversityLanguage: English more
Welcome to Course 2 of Introduction to Applied Cryptography. In this course, you will be introduced to basic mathematical principles and functions that form the foundation for cryptographic and... more
How can we know if the differences in wages between men and women are caused by discrimination or differences in background characteristics? In this PhD-level course we look at causal effects as... more
Welcome to Practical Time Series Analysis! Many of us are \"accidental\" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which... more