This course is a rigorous introduction to statistical inference: probability theory, confidence intervals, and hypothesis tests. The course also covers regression analysis, which is developed in a non ...

An introduction to descriptive statistics, graphing and data analysis, probability laws, discrete and continuous probability distributions, correlation and regression, inferential statistics. No ...

Learning statistics is essential for pursuing a career in data science or analytics. Data scientists and analysts use statistics to uncover the meaning behind data. A spreadsheet with millions of ...

Imagine we had a question: “Do men and women differ on X?” No matter what “X” is—height, empathy, knowledge of 13 th century Spanish history, or anything else—we know that any given man will be ...

Different measures of goodness-of-fit provide information to describe how well models fit the data. However, it’s important to note that these measures have shown modest growth in comparison to the ...

Possibility theory and conditional probability offer complementary perspectives for modelling uncertainty, with each framework contributing distinct advantages. Possibility theory, rooted in fuzzy set ...

Basic statistical concepts presented with emphasis on their relevance to biological and medical investigations. Evaluation is through problem sets, quizzes embedded within asynchronous videos, use of ...

Carnap took the content of a particular sentence or set of sentences to consist in the set of the consequences of the sentence or set. This claim equates meaning with inferential role, but it ...

Imagine we had a question: “Do men and women differ on X?” No matter what “X” is—height, empathy, knowledge of 13 th century Spanish history, or anything else—we know that any given man will be ...