Definition of Unknown Unknown: Unknown is a term used in data science to describe an attribute or value that has yet to be determined. This may be due to a lack of data or because the data is too noisy to be accurately analyzed. In either case, the goal of data science is to identify…
Definition of Universality Universality: Universality is the property of being applicable to a class of objects or phenomena. In data science, this means that a model or algorithm can be used to solve a problem for a wide range of data sets. This makes universality an important property for any data science toolkit.
Definition of Univariate Univariate: A univariate analysis is a data analysis technique that considers only one variable at a time.
Definition of Type II Error Type II error: A type II error, also known as a false negative error, is the incorrect acceptance of a false null hypothesis.
Definition of Type I Error Type I error: A type I error, also known as a false positive error, is the incorrect rejection of a true null hypothesis.
Definition of Two-sample t-test Two-sample t-test: A two-sample t-test is a statistical hypothesis test used to determine whether the means of two samples are statistically different from each other. The test statistic is a t statistic, which is the ratio of the differences between the means of the two samples to the standard error of…
Definition of Time-Series Time-Series: A time-series is a sequence of data points, usually measured at successive points in time. Time-series analysis is the process of examining these data points in order to identify and understand trends and patterns. Time-series data can be used to predict future events, track performance over time, or measure the impact…