Updated on March 16, 2024

Choosing the right adjective to describe *distributions* can significantly impact the perception and understanding of statistical data. Descriptors such as **normal**, **different**, or **angular** can emphasize the nature, shape, or comparison of distributions. Describing a distribution as **spatial** or **continuous** illuminates its properties across dimensions or its uninterrupted nature, respectively. Meanwhile, the term **marginal** may highlight its relevance to the fringes of the dataset. Each of these adjectives adds a unique layer of meaning, enriching our comprehension of complex data. Explore more adjectives that bring out the nuances in distributions below.

normal | |

different | There are different distributions of characteristics within the population. |

angular | The angular distributions of the scattered particles were measured. |

spatial | Spatial distributions are the way in which objects are arranged in space. |

continuous | Continuous distributions are characterized by their probability density functions, which describe the probability of a random variable taking on a specific value. |

marginal | The marginal distributions of the variables are independent. |

conditional | The conditional distributions of the variables X and Y are given by P(X|Y) and P(Y|X), respectively. |

statistical | Many statistical distributions are used in Bayesian inference. |

cumulative | The cumulative distributions are calculated by integrating the probability density function. |

discrete | |

similar | The two samples have similar distributions |

prior | In Bayesian statistics, prior distributions represent existing knowledge about the parameters of a model before any data is observed. |

current | The current distributions in the liquid region are supposed to be provided by the electric double layer. |

theoretical | The theoretical distributions were used to model the data. |

gaussian | The researchers used gaussian distributions to model the distribution of the data. |

observed | Researchers observed distributions of phylogenetic diversity across sites. |

skewed | The skewed distributions were analyzed using a variety of statistical methods. |

uniform | The probability density function of uniform distributions is constant. |

size | The size distributions of nanoparticles were measured using dynamic light scattering. |

possible | We found three possible distributions of polynomials |

posterior | The posterior distributions are calculated using Markov chain Monte Carlo methods. |

exponential | Exponential distributions are commonly used to model the time between events in a Poisson process. |

vertical | Vertical distributions of species are often associated with environmental gradients. |

actual | The actual distributions were quite different from the predicted ones. |

empirical | We used empirical distributions to model the distribution of the data. |

molecular | The experimental setup allowed the observation of molecular distributions close to the Earth's surface. |

joint | The joint distributions of the pairs of specified random variables are presented in the matrix below. |

relative | Variations in measurement parameters will affect relative distributions |

geographical | Scientists use geographical distributions to study the spread of plant and animal species. |

corresponding | The corresponding distributions of the two samples were compared. |

typical | The data follows typical distributions |

multivariate | The multivariate distributions are characterized by their joint probability density function. |

dimensional | Some statistical models require the use of dimensional distributions |

initial | The company used initial distributions to ensure that all shareholders received an equal number of shares. |

geographic | The geographic distributions of species are influenced by a variety of factors, including climate, habitat, and competition. |

occupational | Occupational distributions are strongly influenced by the level of economic development of a country. |

stable | Stable distributions are used in many areas of science and engineering, including finance, economics, and physics. |

identical | The random variables X and Y have identical distributions |

potential | The potential distributions of the sodium ions were calculated using the Poisson-Boltzmann equation. |

random | The student's scores were evenly distributed across the random distributions |

unequal | The unequal distributions of resources have led to widespread poverty and inequality. |

binomial | Binomial distributions are a type of probability distribution that describes the number of successes in a sequence of independent Bernoulli trials. |

bimodal | The data exhibited bimodal distributions suggesting the presence of two distinct populations. |

bivariate | Bivariate distributions are used to model the joint distribution of two random variables. |

narrow | Although the data had narrow distributions the mean values were significantly different |

lognormal | We have found that the athlete's body temperature increases by 99.6 and the data can be fitted to lognormal distributions |

experimental | We used experimental distributions to model the data. |

asymptotic | The asymptotic distributions of the estimators are derived from the central limit theorem. |

regional | The regional distributions of species can be influenced by a variety of factors, including climate, competition, and predation. |

symmetric | |

measured | We analyzed the measured distributions of the parameters of the simulated data. |

univariate | Scientists commonly model this using a variety of univariate distributions |

independent | |

broad | The data has broad distributions across all measured variables. |

standard | |

symmetrical | The symmetrical distributions of the sample data indicate a normal distribution. |

respective | Students in the class performed well in their respective distributions |

time | Researchers analyzed the time distributions of two neural populations during two distinct behavioral tasks. |

arbitrary | The model used arbitrary distributions to generate plausible data. |

minimum | The required minimum distributions from an inherited IRA must be taken each year. |

sum | "The variances of prior and posterior sum distributions is related through the Fisher Information of the likelihood function." |

corporate | The company's corporate distributions have been increasing steadily over the past few years. |

alternative | Alternative distributions allow users to create multiple custom distributions for different applications. |

equal | The funds were allocated with equal distributions to all members. |

subjective | Here are a few subjective distributions with natural frequencies that we can think of, if we want to assign subjective probabilities on the discrete sample space. |

distinct | The measurements have distinct distributions |

exact | The exact distributions of the solutions to the differential equation have been determined. |

radial | The radial distributions of the electron densities are shown. |

hypothetical | The so-called `t` test statistic arises as the ratio of the sample mean difference to the estimated standard deviation of the difference and, under the null hypothesis, has the Student's `t` distribution with degrees of freedom equal to the number of pairs and `p` values can be obtained directly from hypothetical distributions using the cumulative distribution of the `t` distribution. |

tailed | Many real-world phenomena are characterized by tailed distributions |

extreme | The data exhibited extreme distributions suggesting a high degree of variability. |

stress | Engineers analyze stress distributions to ensure structural integrity. |

unimodal | This research contributes to management literature by examining the evolution of alliance portfolios over time and demonstrating the presence of unimodal distributions in alliance frequency. |

calculated | The financial analyst provided calculated distributions to investors. |

square | Many different square distributions can be proposed. |

stationary | The Markov chain has two stationary distributions if and only if it is a reducible Markov chain. |

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