Activation Function : Activation functions are a crucial part of neural networks, as they determine the output of a node or neuron in a neural network. Activation functions determine whether a neuron should be activated or not, based on the input received. Activation functions are essential in neural networks because they allow the network to […]

Accuracy Score : Accuracy score is a metric used to evaluate the performance of a classification model. It is the ratio of the number of correct predictions made by the model to the total number of predictions made. In other words, it measures the proportion of predictions made by the model that are correct. For […]

Adaptive Cluster Sampling : Adaptive cluster sampling is a type of sampling method that is used to select a sample from a population. This method is commonly used in surveys and research studies, as it allows for the selection of a representative sample from a population that is more efficient and cost-effective than other sampling […]

Actuarial statistics : Actuarial statistics is the branch of statistics that focuses on the analysis and modeling of uncertain events, particularly in the fields of insurance, finance, and pension planning. Actuaries use statistical techniques to assess the likelihood and impact of various risks, such as natural disasters, stock market fluctuations, and longevity. They use this […]

Acquiescence bias : Acquiescence bias is a form of response bias that occurs when individuals tend to agree with statements or questions, regardless of their accuracy or truthfulness. This tendency to agree with statements can lead to inaccurate responses and skewed data, resulting in unreliable research findings. One example of acquiescence bias can be seen […]

ACORN : Residential neighborhoods are often classified based on various factors such as the type of homes, the age of the neighborhood, and the socio-economic status of its residents. These classifications help in understanding the characteristics and features of a neighborhood, which in turn helps in determining the quality of life and amenities available in […]

Adjusted treatment means : Adjusted treatment means, also known as adjusted means or adjusted mean differences, are statistical methods used to compare the means of different groups or treatment conditions while controlling for potential confounders or other factors that may affect the results. This is important because without adjusting for such factors, the observed differences […]

Adjacency Matrix : An adjacency matrix is a square matrix used to represent a finite graph. The elements of the matrix indicate whether pairs of vertices are adjacent or not in the graph. In other words, the matrix is used to show the relationship between the vertices of a graph. For example, consider a graph […]

Additive Outlier : An additive outlier is a type of outlier that is caused by the addition of an extreme value to a dataset. This type of outlier can occur in any type of data, including numerical, categorical, and time series data. Additive outliers can have a significant impact on the analysis of a dataset, […]

Additive Model : The additive model is a statistical method used to analyze the relationship between a response variable and one or more predictor variables. In this model, the effects of the predictor variables are assumed to be independent and additive, meaning that the overall effect on the response variable can be calculated by summing […]