Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Functional data analysis (FDA) is the branch of statistics that treats individual observations as continuous functions, curves or surfaces rather than as finite-dimensional vectors. Central to FDA are ...

Multivariate statistical inference encompasses techniques for analysing and drawing conclusions from data in which multiple interrelated variables are observed simultaneously. Unlike univariate ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...

Time series is data collected over time, and statistical learning is a field of statistics and machine learning that develops algorithms to model and interpret this data. Together, they use ...

Successful completion of this course demonstrate your achievement of the following learning outcomes for the MS-DS program: Define a composite hypothesis and the level of significance for a test with ...

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

Social statistics is the branch of statistics devoted to the application and development of quantitative methods tailored to the social and human sciences. Focusing on human behaviour, social ...

Let’s start with a definition of Applied Statistics: Applied Statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an ...