Multistate models : Multistate models are mathematical models used to analyze complex systems with multiple states or conditions. These models are often used in fields such as actuarial science, engineering, and biology to understand and predict the behavior of systems with multiple possible outcomes. One example of a multistate model is a Markov chain. A […]

Multiple time series : A multiple time series is a type of time series data that involves more than one dependent variable. In other words, it is a collection of time series data sets that are related to each other and have a common time frame. This type of time series can provide valuable insights […]

Multiple time response data : Multiple time response data refers to data that is collected at multiple points in time. This type of data is often used to track changes or trends over time, or to identify patterns or trends within a given time period. One example of multiple time response data is tracking the […]

Multiple imputation : Multiple imputation is a statistical technique that is used to account for missing data in a dataset. The method involves generating multiple versions of the dataset, each with different values for the missing data, and then using these different versions to estimate the effects of the missing data on the analysis. One […]

Multiple-frame surveys : Multiple-frame surveys are a type of survey methodology that uses multiple sampling frames in order to increase the representativeness and accuracy of the survey results. This is particularly useful in cases where a single sampling frame may not adequately capture the target population, or when certain subgroups within the population are underrepresented […]

Multinomial logistic regression : Multinomial logistic regression is a type of regression analysis used when there are multiple dependent variables, each with more than two categories. It is a way to predict the probability of an individual belonging to a certain category based on certain predictor variables. For example, a researcher may want to predict […]

Multinomial distribution : The multinomial distribution is a probability distribution that describes the probability of observing a certain combination of outcomes in a series of independent and identically distributed trials. In other words, it is a generalization of the binomial distribution, which only considers two possible outcomes (i.e., success and failure) in each trial. For […]

Multinomial coefficient : The multinomial coefficient is a mathematical concept that is used to represent the number of ways in which objects can be arranged into groups. It is commonly used in combinatorics, the branch of mathematics that deals with the study of counting and arranging objects. For example, suppose we have three different objects, […]

Multimodal distribution : Multimodal distribution refers to a type of data distribution that has multiple peaks or modes. This means that there is more than one value or group of values that occur most frequently in the data set. For example, let’s say we are conducting a study on the heights of adult males and […]

Multilevel models : Multilevel models, also known as hierarchical models or mixed-effects models, are a type of regression analysis that allows for both fixed and random effects. This means that the model can account for both variability that is inherent to the data (random effects) as well as variability that is due to external factors […]