Statistical inference is the process of using data analysis to infer properties of an underlying distribution of probability.[1]Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population.
Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term inference is sometimes used instead to mean "make a prediction, by evaluating an already trained model";[2] in this context inferring properties of the model is referred to as training or learning (rather than inference), and using a model for prediction is referred to as inference (instead of prediction); see also predictive inference.
^Upton, G., Cook, I. (2008) Oxford Dictionary of Statistics, OUP. ISBN 978-0-19-954145-4.
^"TensorFlow Lite inference". The term inference refers to the process of executing a TensorFlow Lite model on-device in order to make predictions based on input data.
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Statisticalinference is the process of using data analysis to infer properties of an underlying distribution of probability. Inferential statistical...
intelligence researchers develop automated inference systems to emulate human inference. Statisticalinference uses mathematics to draw conclusions in the...
A statistical hypothesis test is a method of statisticalinference used to decide whether the data sufficiently support a particular hypothesis. A statistical...
Bayesian inference (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a method of statisticalinference in which Bayes' theorem is used to update the probability...
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Frequentist inference is a type of statisticalinference based in frequentist probability, which treats “probability” in equivalent terms to “frequency”...
generally, statistical models are part of the foundation of statisticalinference. A statistical model is usually specified as a mathematical relationship...
or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups...
still be regarded as statistical parameters of the population, and statistical procedures can still attempt to make inferences about such population...
of statistics. The theory covers approaches to statistical-decision problems and to statisticalinference, and the actions and deductions that satisfy the...
of the Royal Statistical Society, Series B, 33 (2): 256–262. Pawitan, Yudi (2001). In All Likelihood: Statistical Modelling and Inference Using Likelihood...
method Frequentist inferenceStatistical hypothesis testing Null hypothesis Alternative hypothesis P-value Significance level Statistical power Type I and...
translated into several languages. His works include: The Logic of StatisticalInference (1965) A Concise Introduction to Logic (1972) ISBN 039431008X The...
hypothesis about which one wishes to make inference, statisticalinference most often uses: a statistical model of the random process that is supposed...
example, in Bayesian inference, Bayes' theorem can be used to estimate the parameters of a probability distribution or statistical model. Since Bayesian...
field. Statistical analyses based on non-randomly selected samples can lead to erroneous conclusions. The Heckman correction, a two-step statistical approach...
Nonparametric statistics can be used for descriptive statistics or statisticalinference. Nonparametric tests are often used when the assumptions of parametric...
state, "The majority of the problems in statisticalinference can be considered to be problems related to statistical modeling". Relatedly, Cox (2006, p. 197)...
two approaches to statisticalinference: model-based inference and design-based inference. Both approaches rely on some statistical model to represent...
foundations of statistics and is also widely used for statisticalinference. Suppose that we have a statistical model of some data. Let k be the number of estimated...
of statistical analysis is to produce information about some chosen population. In statisticalinference, a subset of the population (a statistical sample)...
to −3.296. Several approaches to statisticalinference for odds ratios have been developed. One approach to inference uses large sample approximations...
learning theory deals with the statisticalinference problem of finding a predictive function based on data. Statistical learning theory has led to successful...
Stack Exchange. Retrieved 2022-06-24. Rao, C. R. (1973). Linear StatisticalInference and Its Applications. New York: Wiley. pp. 527–528. ISBN 0-471-70823-2...
observed statistical laws, and guide the application of statistical conclusions in social and scientific applications. Statisticalinference addresses...
Researchers carry out statistical surveys with a view towards making statisticalinferences about the population being studied; such inferences depend strongly...
reasoning include generalization, prediction, statistical syllogism, argument from analogy, and causal inference. There are also differences in how their results...
Fiducial inference is one of a number of different types of statisticalinference. These are rules, intended for general application, by which conclusions...
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