Probability and Statistics Online Courses for Students

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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 how to evaluate them. This course will also prepare you for the next course in the specialization -...
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural...
This specialization is intended for public health and healthcare professionals, researchers, data analysts, social workers, and others who need a comprehensive concepts-centric biostatistics primer. Those who complete the specialization will be able to read and respond to the scientific...
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. Before beginning the class make sure that you have the following: - A basic understanding of linear...
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level...
In Elicitation: Artifact and Stakeholder Driven Analysis, you will learn to use both recorded and presently unrecorded knowledge in your elicitation techniques. As you get started in finding out about the new product, you must first learn about the product that was (if there was one) and then...
This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple...
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist\'s toolkit. This course covers regression analysis, least...
The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. A large and complex dataset will be provided to learners and the analysis will require the application of a variety of methods and techniques introduced in the...
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 how causal effects are defined, what assumptions about your data and models are necessary, and how...
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 perspective of...
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 framework to analyze these concerns as you examine the ethical and privacy implications of collecting...
Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based...
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 inference. This course covers the basics of creating data products using Shiny, R packages, and...
This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening...
Welcome to Part 3 of Exploring Beethoven\'s Piano Sonatas! I\'m delighted to launch another set of new lectures of this course as Part 3. As before, this class is meant for people of all levels of experience with Beethoven\'s music (including no experience at all!). Remember that you are able to...
Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make...
This course will teach you the basics of developing mobile applications using Mixed and Augmented Reality (MAR) technologies. Through hands-on projects, you\'ll learn practical techniques to rapidly and easily prototype three different applications for Android smartphones and tablets - even with...
This course teaches you the simple principles expert managers use to improve and motivate employee performance. You\'ll never have to avoid telling an employee \"the truth\" again, because the seven techniques we teach will not make employees defensive or afraid. As a manager, or someone who...
With this course you will position your own leadership style and grow your resilience In this course, second course of the \"Inspirational Leadership\" Specialization, you will discover the characteristics of charismatic leadership. You\'ll personally learn how to embody these traits through the...

Probability and Statistics Online Courses for UCLA Students

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