Length-biased data : Length-biased data refers to data sets that are skewed towards longer observations or values. This bias occurs when the data collection process disproportionately focuses on longer observations or values, resulting in a disproportionate representation of these observations in the data set. One example of length-biased data is in the healthcare industry, where […]

Least squares estimation : Least squares estimation is a statistical technique that is used to find the line of best fit for a given set of data. This line of best fit is determined by minimizing the sum of the squares of the vertical distances between the data points and the line. To illustrate this […]

Least squares cross-validation : Least squares cross-validation is a technique used in machine learning to evaluate the performance of a model on a dataset. The goal of this technique is to find the model that minimizes the error between the predicted values and the actual values in the dataset. To understand how least squares cross-validation […]

Least significant difference test : The least significant difference (LSD) test is a statistical method used to compare the means of multiple groups. This test is typically used when conducting an analysis of variance (ANOVA) to determine whether there are significant differences between the means of the groups. For example, imagine that a researcher is […]

Least absolute deviation regression : Least absolute deviation regression, also known as L1 regression, is a type of regression analysis that minimizes the absolute difference between the observed values and the predicted values. This approach is useful in situations where there are outliers in the data, as it is less sensitive to the effects of […]

Leaps-and-bounds algorithm : The Leaps-and-Bounds algorithm is a search method that uses a combination of linear and binary search techniques to efficiently find a target value within a sorted array. This algorithm is particularly useful when searching for a specific value within a large dataset, as it can significantly reduce the number of steps required […]

Lead Time Bias : Lead time bias is a type of bias that occurs when the estimated survival time of a patient is affected by the length of time it takes for their diagnosis to be confirmed. This bias can result in an overestimation of the survival time for patients with longer lead times, as […]

LDU test : An LDU (Lower Diagonal Unit) test matrix is a matrix with the property that all entries below the main diagonal are zero. In other words, an LDU test matrix is a matrix where all entries a[i,j] are zero, whenever i > j. For example, the following is an LDU matrix: [1 0 […]

Law of likelihood : The law of likelihood is a principle in statistics that states that the likelihood of a hypothesis being true is directly proportional to its prior probability and the degree to which it explains the observed data. This means that a hypothesis with a higher prior probability and a good explanation of […]

Law of large numbers : The law of large numbers states that as the sample size of a random variable increases, the average of the sample approaches the true mean of the population. In other words, the more data we collect, the closer our sample mean will be to the true population mean. For example, […]