statistics

Overview This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using...

Overview This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student...

Overview 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 probabilities into posterior probabilities, and be introduced to the underlying theory and...

Overview Statistics is a versatile discipline that has revolutionized the fields of business, engineering, medicine and pure sciences. This course is Part 1 of a 4-part series on Business Statistics, and is ideal for learners who wish to enroll in business programs. The first two courses cover...

Overview Statistics is a versatile discipline that has revolutionized the fields of business, engineering, medicine and pure sciences. This course is Part 2 of a 4-part series on Business Statistics, and is ideal for learners who wish to enroll in business programs. The first two parts cover...

Overview Statistical Inference is the process by which data is used to draw a conclusion or uncover a scientific truth about a population from a sample. This course aims to familiarize the student with several ideas and instruments for statistical inference. It covers fundamental concepts and...

Overview Why do we study statistics? The field of statistics provides professionals and scientists with conceptual foundations and useful techniques for evaluating ideas, testing theories, and - ultimately - uncovering the truth in any situation. This course will familiarize you with data and...

Overview Decision makers often struggle with questions such as: What should be the right price for a product? Which customer is likely to default in his/her loan repayment? Which products should be recommended to an existing customer? Finding right answers to these questions can be challenging...

Overview 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. Problem sets...

Overview The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning. In this course, part of the Data Science...

Overview The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Probabilistic modeling and the related field of statistical inference are the keys to analyzing data and making scientifically sound predictions...

Overview 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...

Overview This course is part of the Microsoft Professional Program Certificate in Data Science. If you’re considering a career as a data analyst, you need to know about histograms, Pareto charts, Boxplots, Bayes’ theorem, and much more. In this applied statistics course, the second in our...

Overview Organisations everywhere want to exploit data to predict behaviours and extract valuable real-world insights. You will learn key statistical elements of data science. You will focus on data exploration and discovery, learning what to look for in data, its limitations and avoiding being...

Overview 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 business processes. The course aim to cover statistical ideas that apply to managers. We...

The world's #1 MOOC platform, Coursera, has shared with me their 12 most popular courses currently available for enrolment. Discover courses in Machine Learning, Data Science, Finance and more from the likes of Stanford, Yale, Johns Hopkins and other top universities. Coursera offers a 7-day...

COURSE DESCRIPTION A conceptual and interpretive public health approach to some of the most commonly used methods from basic statistics. Length: 8 Weeks Effort: 2-3 hours per week Price: FREE (Add a verified certificate for £36) Provider: Johns Hopkins University via Coursera Subject...

COURSE DESCRIPTION A practical and example filled tour of simple and multiple regression techniques (linear, logistic, and Cox PH) for estimation, adjustment and prediction. Length: 8 Weeks Effort: 2-3 hours per week Price: FREE (Add a verified certificate for £36) Provider: Johns Hopkins...

COURSE DESCRIPTION In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute...

COURSE DESCRIPTION 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. Problem...