Box and Whisker plot : A box and whisker plot is a graphical representation of a dataset that displays the distribution of the data and its range. It consists of a box, which represents the middle 50% of the data, and two whiskers, which extend from the box to show the range of the data. […]

Boundary Estimation : Boundary estimation is a statistical method that involves determining the range within which the true value of a population parameter is likely to lie. This range is determined by using sample data to calculate an interval estimate, which is a type of confidence interval. For example, suppose a researcher wants to estimate […]

Bootstrap : Bootstrap is a statistical method used to estimate the sampling distribution of a statistic through the use of resampling techniques. It involves repeatedly sampling with replacement from a dataset, calculating the statistic of interest for each sample, and then using the resulting sample of statistics to estimate the sampling distribution. One of the […]

Boosting : Boosting is a machine learning ensemble method that combines multiple weak learners to create a stronger model. A weak learner is a model that performs slightly better than random guessing. The boosting algorithm works by training the weak learners sequentially, with each subsequent learner trying to correct the mistakes of the previous one. […]

BMI : Body mass index (BMI) is a measure of a person’s weight in relation to their height. It is commonly used to determine whether a person is underweight, normal weight, overweight, or obese. To calculate BMI, a person’s weight in kilograms is divided by their height in meters squared. For example, a person who […]

BLUE : A best linear unbiased estimator (BLUE) is a statistical estimator that satisfies the following three conditions: It is a linear function of the data. This means that the estimator can be expressed as a weighted sum of the observed values, where the weights are constants. For example, the sample mean is a linear […]

Blocking : Blocking is a technique used in data analysis to improve the efficiency and accuracy of statistical models by grouping similar observations together. This helps to reduce noise and improve the signal-to-noise ratio in the data, which in turn can improve the performance of the model. One common example of blocking is the use […]

Block Clustering : Block clustering is a method of grouping data points into clusters based on their spatial proximity. It involves dividing the data space into a grid of blocks, and then assigning each data point to the block that it falls into. This method is useful for identifying patterns and trends within large datasets, […]

Blending : Blending data refers to the process of combining multiple data sources in order to create a comprehensive, cohesive dataset. This technique is often used in data analysis and visualization, as well as in machine learning and other fields of data science. There are several different ways to blend data, depending on the specific […]

Binomial Distribution : The binomial distribution is a probability distribution that describes the likelihood of a specific number of successes in a given number of independent trials. It is named after the binomial coefficient, which represents the number of ways that a certain number of successes can occur within a given number of trials. For […]