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SAMPLING PROBABILITY

  • Sampling (statistics)
  • Selection of data points in statistics

    survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling. Results from probability theory

    Sampling (statistics)

    Sampling (statistics)

    Sampling_(statistics)

  • Sampling probability
  • Theory relating to sampling from finite populations

    in the theory relating to sampling from finite populations, the sampling probability (also known as inclusion probability) of an element or member of

    Sampling probability

    Sampling_probability

  • Simple random sample
  • Sampling technique

    small sample from a large population, sampling without replacement is approximately the same as sampling with replacement, since the probability of choosing

    Simple random sample

    Simple_random_sample

  • Probability-proportional-to-size sampling
  • In survey methodology

    In survey methodology, probability-proportional-to-size (pps) sampling is a sampling process where each element of the population (of size N) has some

    Probability-proportional-to-size sampling

    Probability-proportional-to-size_sampling

  • Survey sampling
  • Statistical selection process

    conducting a probability sample of the household population in the United States are Area Probability Sampling, Random Digit Dial telephone sampling, and more

    Survey sampling

    Survey_sampling

  • Sampling distribution
  • Probability distribution of the possible sample outcomes

    In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic. For an arbitrarily

    Sampling distribution

    Sampling_distribution

  • Top-p sampling
  • Sequence generation sampling technique

    Top-p sampling, also known as nucleus sampling, is a stochastic decoding strategy for generating sequences from autoregressive probabilistic models. It

    Top-p sampling

    Top-p_sampling

  • Probability theory
  • Branch of mathematics concerning probability

    Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations

    Probability theory

    Probability theory

    Probability_theory

  • Inverse transform sampling
  • Basic method for pseudo-random number sampling

    Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov

    Inverse transform sampling

    Inverse transform sampling

    Inverse_transform_sampling

  • Frequentist probability
  • Interpretation of probability

    infinitely many trials. Probabilities can be found (in principle) by a repeatable objective process, as in repeated sampling from the same population

    Frequentist probability

    Frequentist probability

    Frequentist_probability

  • Metropolis–Hastings algorithm
  • Monte Carlo algorithm

    obtaining a sequence of random samples from a probability distribution from which direct sampling is difficult. New samples are added to the sequence in

    Metropolis–Hastings algorithm

    Metropolis–Hastings algorithm

    Metropolis–Hastings_algorithm

  • Sample space
  • Set of all possible outcomes or results of a statistical trial or experiment

    In probability theory, the sample space (also called sample description space, possibility space, or outcome space) of an experiment or random trial is

    Sample space

    Sample space

    Sample_space

  • Probability distribution
  • Mathematical function for the probability a given outcome occurs in an experiment

    In probability theory and statistics, a probability distribution describes how probabilities are assigned to the possible results of a random phenomenon—more

    Probability distribution

    Probability distribution

    Probability_distribution

  • Sampling bias
  • Bias in the sampling of a population

    phenomenon under study rather than to the method of sampling. Medical sources sometimes refer to sampling bias as ascertainment bias. Ascertainment bias has

    Sampling bias

    Sampling bias

    Sampling_bias

  • Inverse probability weighting
  • Statistical technique

    the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used

    Inverse probability weighting

    Inverse_probability_weighting

  • Reservoir sampling
  • Randomized algorithm

    general purpose unequal probability sampling plan". Biometrika. 69 (3): 653–656. doi:10.1093/biomet/69.3.653. Tillé, Yves (2006). Sampling Algorithms. Springer

    Reservoir sampling

    Reservoir_sampling

  • Convenience sampling
  • Sampling from the part of the population close at hand

    sampling (also known as grab sampling, accidental sampling, or opportunity sampling) is a type of non-probability sampling that involves the sample being

    Convenience sampling

    Convenience_sampling

  • Design effect
  • Statistical measure used in survey research

    cluster sampling we can use a two stage sampling in which we sample each cluster (which may be of different sizes) with equal probability, and then sample from

    Design effect

    Design_effect

  • Gibbs sampling
  • Monte Carlo algorithm

    statistics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for sampling from a specified multivariate probability distribution

    Gibbs sampling

    Gibbs_sampling

  • Binomial distribution
  • Probability distribution

    In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes

    Binomial distribution

    Binomial distribution

    Binomial_distribution

  • Probability space
  • Mathematical concept

    formal model of a random process or experiment. A probability space consists of three elements: A sample space, Ω {\displaystyle \Omega } , which is the

    Probability space

    Probability space

    Probability_space

  • Event (probability theory)
  • In statistics and probability theory, set of outcomes to which a probability is assigned

    In probability theory, an event is a subset of outcomes of an experiment (a subset of the sample space) to which a probability is assigned. A single outcome

    Event (probability theory)

    Event (probability theory)

    Event_(probability_theory)

  • Nonprobability sampling
  • Sampling method

    Nonprobability sampling is a form of sampling that does not utilise random sampling techniques where the probability of getting any particular sample may be calculated

    Nonprobability sampling

    Nonprobability_sampling

  • Thompson sampling
  • Type of heuristic technique

    maintain and sample from a posterior distribution over models. As such, Thompson sampling is often used in conjunction with approximate sampling techniques

    Thompson sampling

    Thompson sampling

    Thompson_sampling

  • Rejection sampling
  • Computational statistics technique

    f_{\varpropto }} . The rejection sampling method generates sampling values from a target distribution with probability density function f ( x ) {\displaystyle

    Rejection sampling

    Rejection sampling

    Rejection_sampling

  • Boson sampling
  • Restricted model of non-universal quantum computation

    boson sampling device, which makes it a non-universal approach to linear optical quantum computing. Moreover, while not universal, the boson sampling scheme

    Boson sampling

    Boson_sampling

  • Poisson sampling
  • Survey methodology process

    p_{i}} ). If all first-order inclusion probabilities are equal, Poisson sampling becomes equivalent to Bernoulli sampling, which can therefore be considered

    Poisson sampling

    Poisson_sampling

  • Sampling design
  • finite population sampling, a sampling design specifies for every possible sample its probability of being drawn. Mathematically, a sampling design is denoted

    Sampling design

    Sampling_design

  • Importance sampling
  • Distribution estimation technique

    sampling is also related to umbrella sampling in computational physics. Depending on the application, the term may refer to the process of sampling from

    Importance sampling

    Importance_sampling

  • Probability
  • Number measuring the chance an event occurs

    Probability concerns events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger

    Probability

    Probability

    Probability

  • Gy's sampling theory
  • Gy's sampling theory is a theory about the sampling of materials, developed by Pierre Gy from the 1950s to beginning 2000s in articles and books including:

    Gy's sampling theory

    Gy's_sampling_theory

  • List of statistics articles
  • Sampling design Sampling distribution Sampling error Sampling fraction Sampling frame Sampling probability Sampling risk Samuelson's inequality Sargan test

    List of statistics articles

    List_of_statistics_articles

  • Bootstrapping (statistics)
  • Statistical method

    error, etc.) to sample estimates. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods. Bootstrapping

    Bootstrapping (statistics)

    Bootstrapping_(statistics)

  • Probability density function
  • Description of continuous random distribution

    point in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a "relative probability" that the value

    Probability density function

    Probability density function

    Probability_density_function

  • Markov chain Monte Carlo
  • Calculation of complex statistical distributions

    (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution, one can construct a Markov chain

    Markov chain Monte Carlo

    Markov_chain_Monte_Carlo

  • Glossary of probability and statistics
  • sampling bias sampling distribution The probability distribution, obtained by repeated sampling of the population, of a given statistic. sampling error

    Glossary of probability and statistics

    Glossary_of_probability_and_statistics

  • Realization (probability)
  • Observed value of a random variable

    denote their realizations. In probability theory, a random variable is a function X {\displaystyle X} defined from a sample space Ω {\displaystyle \Omega

    Realization (probability)

    Realization (probability)

    Realization_(probability)

  • Bernoulli sampling
  • Sampling technique

    Bernoulli sampling is therefore a special case of Poisson sampling. In Poisson sampling each element of the population may have a different probability of being

    Bernoulli sampling

    Bernoulli_sampling

  • Power (statistics)
  • Term in statistical hypothesis testing

    factors lead to an expected amount of sampling error. A smaller sampling error could be obtained by larger sample sizes from a less variability population

    Power (statistics)

    Power_(statistics)

  • Variance
  • Statistical measure of how far values spread from their average

    In probability theory and statistics, variance is a measure of dispersion, meaning it is a measure of how far a set of numbers are spread out from their

    Variance

    Variance

    Variance

  • Systematic sampling
  • Statistical method for surveys

    sampling is equal probability sampling (also known as epsem), an equiprobability method. This applies in particular when the sampled units are individuals

    Systematic sampling

    Systematic_sampling

  • Statistics
  • Study of collection and analysis of data

    Sampling theory is part of the mathematical discipline of probability theory. Probability is used in mathematical statistics to study the sampling distributions

    Statistics

    Statistics

    Statistics

  • Ewens's sampling formula
  • Sampling formula which describes the probabilities of alleles in a sample

    sampling formula describes the probabilities associated with counts of how many different alleles are observed a given number of times in the sample.

    Ewens's sampling formula

    Ewens's_sampling_formula

  • Conditional probability
  • Probability of an event occurring, given that another event has already occurred

    In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption

    Conditional probability

    Conditional probability

    Conditional_probability

  • Markov chain
  • Random process independent of past history

    as Markov chain Monte Carlo, which are used for simulating sampling from complex probability distributions, and have found application in areas including

    Markov chain

    Markov chain

    Markov_chain

  • Monte Carlo method
  • Probabilistic problem-solving algorithm

    filtering equation). In other instances, a flow of probability distributions with an increasing level of sampling complexity arise (path spaces models with an

    Monte Carlo method

    Monte Carlo method

    Monte_Carlo_method

  • Path tracing
  • Computer graphics method

    the inverse probability factor (required for importance sampling) cancel. Otherwise, direction sampling usually tries to use probabilities proportional

    Path tracing

    Path tracing

    Path_tracing

  • Tobit model
  • Statistical model for censored regressands

    determined threshold. For a sample that, as in Tobin's original case, was censored from below at zero, the sampling probability for each non-limit observation

    Tobit model

    Tobit_model

  • Standard error
  • Statistical property

    standard deviation of its sampling distribution. The standard error is often used in calculations of confidence intervals. The sampling distribution of a mean

    Standard error

    Standard error

    Standard_error

  • Poker probability
  • Chances of card combinations in poker

    the probability of each type of 5-card hand can be computed by calculating the proportion of hands of that type among all possible hands. Probability and

    Poker probability

    Poker_probability

  • Cluster sampling
  • Sampling methodology in statistics

    specific sample size). A third possible solution is to use probability proportionate to size sampling. In this sampling plan, the probability of selecting

    Cluster sampling

    Cluster sampling

    Cluster_sampling

  • Confidence interval
  • Range to estimate an unknown parameter

    {\textstyle (u(X),v(X))} has a probability γ {\textstyle \gamma } of covering the value of θ {\textstyle \theta } in repeated sampling. In many applications,

    Confidence interval

    Confidence interval

    Confidence_interval

  • Probability axioms
  • Foundations of probability theory

    The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. Like all axiomatic

    Probability axioms

    Probability axioms

    Probability_axioms

  • Poisson distribution
  • Discrete probability distribution

    In probability theory and statistics, the Poisson distribution (/ˈpwɑːsɒn/) is a discrete probability distribution that expresses the probability of a

    Poisson distribution

    Poisson distribution

    Poisson_distribution

  • Almost surely
  • Probability saying

    "almost everywhere" in measure theory. In probability experiments on a finite sample space with a non-zero probability for each outcome, there is no difference

    Almost surely

    Almost_surely

  • Statistical inference
  • Process of using data analysis for predicting population data from sample data

    also of importance: in survey sampling, use of sampling without replacement ensures the exchangeability of the sample with the population; in randomized

    Statistical inference

    Statistical_inference

  • Heckman correction
  • Statistical technique correcting sampling bias

    Conceptually, this is achieved by explicitly modelling the individual sampling probability of each observation (the so-called selection equation) together with

    Heckman correction

    Heckman_correction

  • Exponential distribution
  • Probability distribution

    In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance

    Exponential distribution

    Exponential distribution

    Exponential_distribution

  • Mode (statistics)
  • Value that appears most often in a set of data

    is a discrete random variable, the mode is the value x at which the probability mass function P(X) takes its maximum value, i.e., x = argmaxxi P(X =

    Mode (statistics)

    Mode_(statistics)

  • Quota sampling
  • Survey sampling method

    This second step makes the technique non-probability sampling. In quota sampling, there is non-random sample selection and this can be unreliable. For

    Quota sampling

    Quota_sampling

  • Bayesian probability
  • Interpretation of probability

    Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is an interpretation of the concept of probability, in which, instead of frequency or

    Bayesian probability

    Bayesian_probability

  • Beta distribution
  • Probability distribution

    In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1)

    Beta distribution

    Beta distribution

    Beta_distribution

  • Outcome (probability)
  • Possible result of an experiment or trial

    In probability theory, an outcome is a possible result of an experiment or trial. Each possible outcome of a particular experiment is a unique random

    Outcome (probability)

    Outcome (probability)

    Outcome_(probability)

  • Stochastic process
  • Collection of random variables

    In probability theory and related fields a stochastic (/stəˈkæstɪk/) or random process is a mathematical object usually defined as a family of random

    Stochastic process

    Stochastic process

    Stochastic_process

  • Elementary event
  • Event that contains only one outcome

    probability theory, an elementary event, also called an atomic event or sample point, is an event which contains only a single outcome in the sample space

    Elementary event

    Elementary event

    Elementary_event

  • Odds ratio
  • Statistic quantifying the association between two events

    sample approximations to the sampling distribution of the log odds ratio (the natural logarithm of the odds ratio). If we use the joint probability notation

    Odds ratio

    Odds_ratio

  • Hypergeometric distribution
  • Discrete probability distribution

    recount. The sampling rates are usually defined by law, not statistical design, so for a legally defined sample size n, what is the probability of missing

    Hypergeometric distribution

    Hypergeometric distribution

    Hypergeometric_distribution

  • Outline of statistics
  • Overview of and topical guide to statistics

    Statistical survey Opinion poll Sampling theory Sampling distribution Stratified sampling Quota sampling Cluster sampling Biased sample Spectrum bias Survivorship

    Outline of statistics

    Outline_of_statistics

  • Non-uniform random variate generation
  • Generating pseudo-random numbers that follow a probability distribution

    pseudo-random number sampling is the numerical practice of generating pseudo-random numbers (PRN) that follow a given probability distribution. Methods

    Non-uniform random variate generation

    Non-uniform_random_variate_generation

  • Chi-squared test
  • Statistical hypothesis test

    sampling distribution (if the null hypothesis is true) of the test statistic approximates a chi-squared distribution more and more closely as sample sizes

    Chi-squared test

    Chi-squared test

    Chi-squared_test

  • Continuous uniform distribution
  • Uniform distribution on an interval

    In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions

    Continuous uniform distribution

    Continuous uniform distribution

    Continuous_uniform_distribution

  • Sampling fraction
  • Ratio of sample size to population size

    In sampling theory, the sampling fraction is the ratio of sample size to population size or, in the context of stratified sampling, the ratio of the sample

    Sampling fraction

    Sampling_fraction

  • Prior probability
  • Distribution of an uncertain quantity

    A prior probability distribution (often simply called the prior probability, prior distribution, or prior) of an uncertain quantity is its assumed probability

    Prior probability

    Prior_probability

  • Central limit theorem
  • Fundamental theorem in probability theory and statistics

    probability theory, the central limit theorem (CLT) states that, under appropriate conditions, the distribution of a normalized version of the sample

    Central limit theorem

    Central limit theorem

    Central_limit_theorem

  • Likelihood function
  • Function related to statistics and probability theory

    calculating the probability of seeing that data under different parameter values of the model. It is constructed from the joint probability distribution

    Likelihood function

    Likelihood_function

  • Boy or girl paradox
  • Paradox in probability theory

    The boy or girl paradox surrounds a set of questions in probability theory, which are also known as the two children problem, Mr. Smith's children and

    Boy or girl paradox

    Boy or girl paradox

    Boy_or_girl_paradox

  • Scoring rule
  • Measure for evaluating probabilistic forecasts

    the CRPS via Monte Carlo sampling (through approximating the expectation value). Furthermore, when the cumulative probability function F {\displaystyle

    Scoring rule

    Scoring rule

    Scoring_rule

  • Student's t-distribution
  • Probability distribution

    probability theory and statistics, Student's t distribution (or simply the t distribution) t ν {\displaystyle t_{\nu }} is a continuous probability distribution

    Student's t-distribution

    Student's t-distribution

    Student's_t-distribution

  • Statistical distance
  • Distance between two statistical objects

    variables, or two probability distributions or samples, or the distance can be between an individual sample point and a population or a wider sample of points

    Statistical distance

    Statistical_distance

  • Distance sampling
  • Methods for estimating the density and/or abundance of populations

    CUP ISBN 0-521-81099-X (entry for distance sampling) Buckland, S. T. (2004). Advanced distance sampling. Oxford University Press. "Distance project website"

    Distance sampling

    Distance_sampling

  • Experiment (probability theory)
  • Procedure that can be infinitely repeated, with a well-defined set of outcomes

    In probability theory, an experiment or trial (see below) is the mathematical model of any procedure that can be infinitely repeated and has a well-defined

    Experiment (probability theory)

    Experiment (probability theory)

    Experiment_(probability_theory)

  • Median
  • Middle quantile of a data set or probability distribution

    separating the higher half from the lower half of a data sample, a population, or a probability distribution. For a data set, it may be thought of as the

    Median

    Median

    Median

  • Bayesian statistics
  • Theory and paradigm of statistics

    field of statistics based on the Bayesian interpretation of probability, where probability expresses a degree of belief in an event. The degree of belief

    Bayesian statistics

    Bayesian_statistics

  • Empirical probability
  • Probability estimate

    In probability theory and statistics, the empirical probability or experimental probability of an event is an estimate of the probability of the event

    Empirical probability

    Empirical_probability

  • Law of large numbers
  • Averages of repeated trials converge to the expected value

    In probability theory, the law of large numbers is a mathematical law which states that the average of the results obtained from a large number of independent

    Law of large numbers

    Law of large numbers

    Law_of_large_numbers

  • Birthday problem
  • Probability of shared birthdays

    In probability theory, the birthday problem asks for the probability that, in a set of n randomly chosen people, at least two will share the same birthday

    Birthday problem

    Birthday problem

    Birthday_problem

  • Standard deviation
  • Measure of variation in statistics

    The standard deviation of a random variable, sample, statistical population, data set or probability distribution is the square root of its variance

    Standard deviation

    Standard deviation

    Standard_deviation

  • Acceptance sampling
  • Common quality control technique

    Acceptance sampling uses statistical sampling to determine whether to accept or reject a production lot of material. It has been a common quality control

    Acceptance sampling

    Acceptance_sampling

  • Probability integral transform
  • Probability theory operation

    In probability theory, the probability integral transform (also known as universality of the uniform) relates to the result that data values that are

    Probability integral transform

    Probability_integral_transform

  • Independence (probability theory)
  • When the occurrence of one event does not affect the likelihood of another

    Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically

    Independence (probability theory)

    Independence (probability theory)

    Independence_(probability_theory)

  • Probability of superiority
  • The probability of superiority or common language effect size is the probability that, when sampling a pair of observations from two groups, the observation

    Probability of superiority

    Probability_of_superiority

  • Bias of an estimator
  • Statistical property

    results will not be "unbiased" in sampling theory terms. But the results of a Bayesian approach can differ from the sampling theory approach even if the Bayesian

    Bias of an estimator

    Bias_of_an_estimator

  • Hamiltonian Monte Carlo
  • Sampling algorithm

    obtaining a sequence of random samples whose distribution converges to a target probability distribution that is difficult to sample directly. This sequence

    Hamiltonian Monte Carlo

    Hamiltonian Monte Carlo

    Hamiltonian_Monte_Carlo

  • Law of total probability
  • Concept in probability theory

    In probability theory, the law (or formula) of total probability is a fundamental rule relating marginal probabilities to conditional probabilities. It

    Law of total probability

    Law of total probability

    Law_of_total_probability

  • Coverage probability
  • Concept in statistical estimation theory

    coverage probability is the probability that a prediction interval will include an out-of-sample value of the random variable. The coverage probability can

    Coverage probability

    Coverage_probability

  • Selection bias
  • Bias in a statistical analysis due to non-random selection

    information Sampling bias – Bias in the sampling of a population Sampling probability – Theory relating to sampling from finite populations Selective exposure

    Selection bias

    Selection_bias

  • Notation in probability and statistics
  • Probability theory and statistics have some commonly used conventions, in addition to standard mathematical notation and mathematical symbols. Random

    Notation in probability and statistics

    Notation_in_probability_and_statistics

  • Sample size determination
  • Statistical considerations on how many observations to make

    complicated sampling techniques, such as stratified sampling, the sample can often be split up into sub-samples. Typically, if there are H such sub-samples (from

    Sample size determination

    Sample_size_determination

  • Posterior probability
  • Conditional probability used in Bayesian statistics

    The posterior probability is a type of conditional probability that results from updating the prior probability with information summarized by the likelihood

    Posterior probability

    Posterior_probability

  • Fisher's exact test
  • Statistical significance test

    women enter our sample independently of whether or not they are studiers, then this hypergeometric formula gives the conditional probability of observing

    Fisher's exact test

    Fisher's_exact_test

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Online names & meanings

  • Sadashiv
  • Boy/Male

    Hindu

    Sadashiv

    Pure, Eternally pure

  • Ori
  • Boy/Male

    Hebrew

    Ori

    My light.

  • Heemansh
  • Boy/Male

    Hindu, Indian

    Heemansh

    Lord Shiva

  • Valyn
  • Girl/Female

    Latin

    Valyn

    Strong.

  • Bjame
  • Boy/Male

    Norse

    Bjame

    Bear.

  • Shmoodah
  • Girl/Female

    Arabic, Muslim

    Shmoodah

    Diamond

  • Tikshna
  • Boy/Male

    Hindu, Indian

    Tikshna

    Sharp

  • Easlick
  • Surname or Lastname

    English (Devon and Cornwall)

    Easlick

    English (Devon and Cornwall) : variant of Eslick.

  • Malchom
  • Boy/Male

    Australian, Biblical

    Malchom

    Their King; Their Counselor

  • Lovdeep
  • Girl/Female

    Indian, Punjabi, Sikh

    Lovdeep

    Attachment to Illumination

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Other words and meanings similar to

SAMPLING PROBABILITY

AI search in online dictionary sources & meanings containing SAMPLING PROBABILITY

SAMPLING PROBABILITY

  • Tamper
  • n.

    An instrument used in tamping; a tamping iron.

  • Dumpling
  • n.

    A roundish mass of dough boiled in soup, or as a sort of pudding; often, a cover of paste inclosing an apple or other fruit, and boiled or baked; as, an apple dumpling.

  • Saddling
  • p. pr. & vb. n.

    of Saddle

  • Rambling
  • a.

    Roving; wandering; discursive; as, a rambling fellow, talk, or building.

  • Rimpling
  • p. pr. & vb. n.

    of Rimple

  • Saibling
  • n.

    A European mountain trout (Salvelinus alpinus); -- called also Bavarian charr.

  • Rampler
  • a.

    Roving; rambling.

  • Skimble-scamble
  • a.

    Rambling; disorderly; unconnected.

  • Loose
  • superl.

    Unconnected; rambling.

  • Dicing
  • n.

    Gambling with dice.

  • Tamping
  • n.

    The material used in tamping. See Tamp, v. t., 1.

  • Scambling
  • p. pr. & vb. n.

    of Scamble

  • Hell
  • v. t.

    A gambling house.

  • Sailing
  • n.

    The art of managing a vessel; seamanship; navigation; as, globular sailing; oblique sailing.

  • Shambling
  • a.

    Characterized by an awkward, irregular pace; as, a shambling trot; shambling legs.

  • Torgoch
  • n.

    The saibling.

  • Rumpling
  • p. pr. & vb. n.

    of Rumple

  • Trampling
  • p. pr. & vb. n.

    of Trample

  • sapling
  • n.

    A young tree.

  • Searcher
  • n.

    An implement for sampling butter; a butter trier.