Adjectives for Distributions

Adjectives For Distributions

Discover the most popular adjectives for describing distributions, complete with example sentences to guide your usage.

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.
differentThere are different distributions of characteristics within the population.
angularThe angular distributions of the scattered particles were measured.
spatialSpatial distributions are the way in which objects are arranged in space.
continuousContinuous distributions are characterized by their probability density functions, which describe the probability of a random variable taking on a specific value.
marginalThe marginal distributions of the variables are independent.
conditionalThe conditional distributions of the variables X and Y are given by P(X|Y) and P(Y|X), respectively.
statisticalMany statistical distributions are used in Bayesian inference.
cumulativeThe cumulative distributions are calculated by integrating the probability density function.
similarThe two samples have similar distributions
priorIn Bayesian statistics, prior distributions represent existing knowledge about the parameters of a model before any data is observed.
currentThe current distributions in the liquid region are supposed to be provided by the electric double layer.
theoreticalThe theoretical distributions were used to model the data.
gaussianThe researchers used gaussian distributions to model the distribution of the data.
observedResearchers observed distributions of phylogenetic diversity across sites.
skewedThe skewed distributions were analyzed using a variety of statistical methods.
uniformThe probability density function of uniform distributions is constant.
sizeThe size distributions of nanoparticles were measured using dynamic light scattering.
possibleWe found three possible distributions of polynomials
posteriorThe posterior distributions are calculated using Markov chain Monte Carlo methods.
exponentialExponential distributions are commonly used to model the time between events in a Poisson process.
verticalVertical distributions of species are often associated with environmental gradients.
actualThe actual distributions were quite different from the predicted ones.
empiricalWe used empirical distributions to model the distribution of the data.
molecularThe experimental setup allowed the observation of molecular distributions close to the Earth's surface.
jointThe joint distributions of the pairs of specified random variables are presented in the matrix below.
relativeVariations in measurement parameters will affect relative distributions
geographicalScientists use geographical distributions to study the spread of plant and animal species.
correspondingThe corresponding distributions of the two samples were compared.
typicalThe data follows typical distributions
multivariateThe multivariate distributions are characterized by their joint probability density function.
dimensionalSome statistical models require the use of dimensional distributions
initialThe company used initial distributions to ensure that all shareholders received an equal number of shares.
geographicThe geographic distributions of species are influenced by a variety of factors, including climate, habitat, and competition.
occupationalOccupational distributions are strongly influenced by the level of economic development of a country.
stableStable distributions are used in many areas of science and engineering, including finance, economics, and physics.
identicalThe random variables X and Y have identical distributions
potentialThe potential distributions of the sodium ions were calculated using the Poisson-Boltzmann equation.
randomThe student's scores were evenly distributed across the random distributions
unequalThe unequal distributions of resources have led to widespread poverty and inequality.
binomialBinomial distributions are a type of probability distribution that describes the number of successes in a sequence of independent Bernoulli trials.
bimodalThe data exhibited bimodal distributions suggesting the presence of two distinct populations.
bivariateBivariate distributions are used to model the joint distribution of two random variables.
narrowAlthough the data had narrow distributions the mean values were significantly different
lognormalWe have found that the athlete's body temperature increases by 99.6 and the data can be fitted to lognormal distributions
experimentalWe used experimental distributions to model the data.
asymptoticThe asymptotic distributions of the estimators are derived from the central limit theorem.
regionalThe regional distributions of species can be influenced by a variety of factors, including climate, competition, and predation.
measuredWe analyzed the measured distributions of the parameters of the simulated data.
univariateScientists commonly model this using a variety of univariate distributions
broadThe data has broad distributions across all measured variables.
symmetricalThe symmetrical distributions of the sample data indicate a normal distribution.
respectiveStudents in the class performed well in their respective distributions
timeResearchers analyzed the time distributions of two neural populations during two distinct behavioral tasks.
arbitraryThe model used arbitrary distributions to generate plausible data.
minimumThe 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."
corporateThe company's corporate distributions have been increasing steadily over the past few years.
alternativeAlternative distributions allow users to create multiple custom distributions for different applications.
equalThe funds were allocated with equal distributions to all members.
subjectiveHere 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.
distinctThe measurements have distinct distributions
exactThe exact distributions of the solutions to the differential equation have been determined.
radialThe radial distributions of the electron densities are shown.
hypotheticalThe 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.
tailedMany real-world phenomena are characterized by tailed distributions
extremeThe data exhibited extreme distributions suggesting a high degree of variability.
stressEngineers analyze stress distributions to ensure structural integrity.
unimodalThis research contributes to management literature by examining the evolution of alliance portfolios over time and demonstrating the presence of unimodal distributions in alliance frequency.
calculatedThe financial analyst provided calculated distributions to investors.
squareMany different square distributions can be proposed.
stationaryThe Markov chain has two stationary distributions if and only if it is a reducible Markov chain.

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