Incubation period : The incubation period refers to the time it takes for symptoms of a disease to appear after an individual has been exposed to a pathogen. This period can vary greatly depending on the type of disease and the individual’s susceptibility to infection. One example of an incubation period is the flu. After […]

Inclusion and Exclusion Criteria : Inclusion criteria and exclusion criteria are essential components of clinical research studies. These criteria help researchers to define the population they want to study, identify participants who are eligible to participate in the study, and exclude those who are not suitable for the study. Inclusion criteria are the characteristics or […]

Incidental Parameter Problem : The incidental parameter problem, also known as the “nuisance parameter” problem, arises when researchers are trying to estimate the effects of an independent variable on a dependent variable, but other variables (incidental parameters) are also present and may influence the results. This can lead to biased or misleading estimates of the […]

Incidence : Incidence refers to the frequency or rate at which a particular event or phenomenon occurs within a given population or group. In other words, it is a measure of the number of new cases of a particular condition or disease that occur within a specific time period. For example, the incidence of influenza […]

Imputation : Imputation is the process of replacing missing data with estimated values in order to increase the sample size and improve the accuracy of the results. This is important because missing data can lead to biased and unreliable results, particularly in statistical analyses. One example of imputation is the use of mean substitution, which […]

Improper Prior Distribution : Improper prior distributions are those that do not integrate to 1, or do not have a finite mean or variance. This means that the probabilities assigned to certain values in the distribution do not sum to 1, or that the distribution does not have a well-defined center or spread. Improper prior […]

Imprecise Probabilities : Imprecise probabilities refer to situations where the exact probability of an event occurring is not known, but a range of possible probabilities can be estimated. This type of probability is often used in situations where there is uncertainty or limited information available. One example of imprecise probabilities is in weather forecasting. Meteorologists […]

Imperfect Detectability : Imperfect detectability refers to the inability of a system or process to accurately and consistently detect certain events or occurrences. This can lead to errors and inaccuracies in the data collected and analyzed, resulting in unreliable or misleading conclusions. One example of imperfect detectability is in the use of security cameras to […]

Immigration-emigration models : Immigration-emigration models are used to analyze the flow of people in and out of a particular area or country. These models help policymakers and researchers understand the factors that drive immigration and emigration, as well as the potential impacts on the population and economy of the area in question. One example of […]

Ignorability: Ignorability is a statistical concept that refers to the condition in which certain factors or variables can be “ignored” or left out of a statistical analysis without affecting the validity of the results. This is because the factors or variables are considered to be “random” or “not relevant” to the analysis. For example, imagine […]