Hot deck : Hot deck imputation is a method of handling missing data in statistical analysis. It is based on the idea of using available data from similar cases to infer the missing values in a given case. Here are two examples of how hot deck imputation can be used: Example 1: Imagine that you […]

Hosmer-Lemeshow test : The Hosmer-Lemeshow test is a statistical method used to evaluate the goodness of fit of a binary logistic regression model. This test is commonly used in medical research to assess the predictive ability of a model in terms of its ability to accurately classify patients into different categories, such as diseased or […]

Homogeneous : In data science, the term “homogeneous” refers to data that is of the same type or has similar characteristics. This means that all the data in a given dataset belongs to the same category or follows the same format. This is in contrast to heterogeneous data, which is data that is made up […]

Hit Rate : Discrimination analysis is a statistical technique used to identify and measure the impact of discriminatory practices on the outcomes of a particular group or individuals. In this context, hit rate refers to the proportion of individuals from a specific group who are correctly identified as belonging to that group by the analysis. […]

Histogram : A histogram is a graphical representation of data that displays the frequency or number of observations within a specified range of values, called bins. It is used to show the distribution of data and to identify any patterns or trends in the data. For example, imagine we are interested in analyzing the heights […]

Hierarchical Models : Hierarchical models, also known as hierarchical linear models, are a type of statistical modeling technique used to analyze data that is structured in a hierarchical or nested format. These models are particularly useful for analyzing data that has multiple levels of nesting, such as data collected from multiple schools within multiple districts, […]

Hierarchical Likelihood : Hierarchical likelihood is a statistical method that allows for the incorporation of prior knowledge or information into the likelihood calculation. This can be useful in situations where there is uncertainty or lack of data, as it allows for more accurate predictions or estimates. One example of hierarchical likelihood is in the study […]

High Throughput Data : High throughput data refers to a large amount of data that is generated, processed, and analyzed quickly and efficiently. This type of data is commonly used in fields such as genomics, finance, and social media, where large amounts of data are generated and need to be analyzed in real time. One […]

High Dimensional Data : High dimensional data refers to data that has a large number of features or variables. For example, a dataset with 100 columns or features would be considered high dimensional. This is in contrast to low dimensional data, which has only a few features. One example of high dimensional data is a […]

High Breakdown Methods : In robust statistics, high breakdown methods are statistical methods that have a high breakdown point, which is the maximum fraction of outliers that the method can handle before it becomes substantially less effective. This means that these methods are resistant to the effects of outliers, which are data points that are […]