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.

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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