Examples of using Statistical inference in English and their translations into German
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Statistical Inference is a logical continuation to the descriptive statistics.
It combines computer vision, pattern recognition, statistical inference and optics.
Statistical inference methods for behavioral genetics and neuroeconomics>> more.
Dickhaus, Humboldt-Universität zu Berlin: Structural simultaneous statistical inference more….
Statistical Inference: This group performs the most commonstatistical inference procedures of confidence intervals and hypothesis tests.
Reasons enough for our scientists to invent better approaches for statistical inference in fMRI.
The most widely used statistical inference procedures were invented more than 10 years ago and are not well suited for handling state-of-the art high-resolution neuroimaging data.
Machine Learning: To strip our knowledge-bases of their secrets we use statistical inference and machine learning approaches.
And more likely than not, these observations would have been from different telescopes,requiring considerable effort to allow for systematic comparisons and statistical inferences.
Contributions==Christian Genest is best known for developing models and statistical inference techniques for studying the dependence between variables through the concept of copula.
For these countries there exists over 40 observations on a quarterly basis,which should be enough to make valid statistical inferences.
During this period[at University College, London]Hsu wrote a remarkable series of papers on statistical inference which show the strong influence of the Neyman-Pearson point of view.
We develop simulation and statistical inference methods, including geographic and palaeoenvironmental modeling, to create a unified framework for human demographic inference. .
The workgroup on statistical inverse problems deals withsolutions to this problem and, particularly, with statistical inference methods in such models.
Works==*"On the Use andInterpretation of certain Test Criteria for the Purposes of Statistical Inference"(coauthor Jerzy Neyman in Biometrika, 1928)*"The History of statistics in the XVIIth and XVIIIth centuries" 1929.
You will obtain the required skills to solve real-world problems using methods of algorithm design, machine learning,artificial intelligence, statistical inference, operations research, and optimization.
The way samples areselected from a population is very important for statistical inference, since we use the probability of a sample to infer the characteristics of the sample population.
Financial Econometrics This module aims to introduce participants to the fundamental econometric tools for empirical modelling,accustom them with applying these tools to estimation, statistical inference, and forecasting in financial markets;
He laughs,"I used to be a little nerd."He continues with his credentials,"Artificial intelligence at the University of California; statistical inference at Hopkins University; quantum mechanics and quantum computation at the University of California at Berkeley; machine learning, introduction to logic, exploratory data analysis, statistical thinking for data science and analytics….
During this time he made important contributions to the theory of multiple tests for high-dimensional, spatially and time dependent, complex structured data,as well as to simultaneous statistical inference in general, which also continues to be the focus of his research.
The survey need not be carried out if the Member States have information from other appropriate sources or Member States are able toproduce estimates of necessary data using statistical inference methods where some or all of the characteristics have not been observed for all the units for which the statistics are to be compiled.
Probabilistic Finger-printing Probabilistic tracking depends upon collecting non-personal data regarding device attributes like operating system, device make and model, IP addresses, adrequests and location data, and making statistical inferences to link multiple devices to a single user.
The project team develops and validates systematic approaches to infer the molecular bases of mitochondrial diseases in individual patients by combining genetics,functional genomics, and statistical causal inference.