Results 271 to 280 of about 29,999,610 (319)
Some of the next articles are maybe not open access.
2019
In this chapter, we present statistical modelling approaches for predictive tasks in business and science. Most prominent is the ubiquitous multiple linear regression approach where coefficients are estimated using the ordinary least squares algorithm. There are many derivations and generalizations of that technique. In the form of logistic regression,
Dettling, Marcel, Ruckstuhl, Andreas
openaire +2 more sources
In this chapter, we present statistical modelling approaches for predictive tasks in business and science. Most prominent is the ubiquitous multiple linear regression approach where coefficients are estimated using the ordinary least squares algorithm. There are many derivations and generalizations of that technique. In the form of logistic regression,
Dettling, Marcel, Ruckstuhl, Andreas
openaire +2 more sources
2008
Statistical models provide an alternative approach to using dynamical models in seasonal climate forecasting. In statistical models relationships between one set of data, the predictors, and a second set, the predictands, are sought. Common predictands include seasonal mean temperatures and accumulated precipitation, and are typically predicted using ...
Mason, Simon J., Baddour, Omar
openaire +1 more source
Statistical models provide an alternative approach to using dynamical models in seasonal climate forecasting. In statistical models relationships between one set of data, the predictors, and a second set, the predictands, are sought. Common predictands include seasonal mean temperatures and accumulated precipitation, and are typically predicted using ...
Mason, Simon J., Baddour, Omar
openaire +1 more source
Statistical power in two-level models: A tutorial based on Monte Carlo simulation.
Psychological methods, 2019The estimation of power in two-level models used to analyze data that are hierarchically structured is particularly complex because the outcome contains variance at two levels that is regressed on predictors at two levels.
Matthias G. Arend, Thomas Schäfer
semanticscholar +1 more source
2020
This chapter describes the application of statistical concepts with illustration about statistical models, probability, normal distribution, and analysis of variance (ANOVA). Statistical analysis is an important action process in research that deals with data. It follows well-defined, systematic, and mathematical procedures and rules.
Mukhtar Ahmed, Mukhtar Ahmed
openaire +2 more sources
This chapter describes the application of statistical concepts with illustration about statistical models, probability, normal distribution, and analysis of variance (ANOVA). Statistical analysis is an important action process in research that deals with data. It follows well-defined, systematic, and mathematical procedures and rules.
Mukhtar Ahmed, Mukhtar Ahmed
openaire +2 more sources
On Statistical Model Validation
Journal of Dynamic Systems, Measurement, and Control, 1996In this paper we formulate a particular statistical model validation problem in which we wish to determine the probability that a certain hypothesized parametric uncertainty model is consistent with a given input-output data record. Using a Bayesian approach and ideas from the field of hypothesis testing, we show that in many cases of interest this ...
Lawton H. Lee, Kameshwar Poolla
openaire +3 more sources
1994
Linear models form the core of classical statistics and are still the basis of much of statistical practice; many modern modelling and analytical techniques build on the methodology developed for linear models.
B. D. Ripley, W. N. Venables
openaire +2 more sources
Linear models form the core of classical statistics and are still the basis of much of statistical practice; many modern modelling and analytical techniques build on the methodology developed for linear models.
B. D. Ripley, W. N. Venables
openaire +2 more sources
‘Statistics-for’ and ‘Statistics-with’ Agent Models
2021Humankind often sees patterns where none exist (The name for this is pareidolia and it explains among other things why we see faces on the surface of the Moon and Mars, and can make out cars, cats and coffee cups among the clouds.). Statistical tests exist to overcome this and reveal true relationships among variables while quantifying their strength ...
openaire +2 more sources
Statistics for a Diagnostic Model
Biometrics, 1961In recent years, several methods have been proposed for making medical diagnoses by machine (Ledley and Lusted [1959], Crumb and Rupe [1959]). A method devised by Brodman et al. [1959, 1960] has been used to program a high-speed electronic computer for making presumptive medical diagnoses using only information relating to the age, sex, and responses ...
Keeve Brodman, Adrianus J. van Woerkom
openaire +3 more sources
Statistical models and statistical inference
1981In the previous chapter we have seen how a simple statistical model can be fitted to data by estimating the unknown parameters and then making checks with residuals. After we have done this, various questions can be answered in terms of the fitted model.
openaire +2 more sources
On regularity for statistical models
Canadian Journal of Statistics, 1985AbstractSome recent discussions of the logic involved in statistical inference have focussed on the given (i. e. the statistical model and the data) and the role of the common reduction principles (namely conditionality, likelihood, and sufficiency). The minimum statistical model, a class of probability measures on a measurable space, can yield many ...
G. Monette, Michael Evans, Donald Fraser
openaire +3 more sources