Examples of using Statistical inference in English and their translations into Chinese
{-}
-
Political
-
Ecclesiastic
-
Programming
Statistical inference.
Theories of statistical inference.
This justifies the use of large random samples in statistical inference.
Any statistical inference requires some assumptions.
Exploratory analysis, planning a study, probability, and statistical inference.
Statistical inference concepts such as p-values and confidence intervals rely on randomness.
Complete a research project that employs simple statistical inference and modeling techniques.
Thesis: Statistical inference for template-based protein structure prediction(June 2013).
The book is intended to be alow cost introduction to the important field of statistical inference.
Statistical inference for Pearson's correlation coefficient is sensitive to the data distribution.
A research project that employs simple statistical inference and modeling techniques will be assigned.
Statistical inference for Pearson's correlation coefficient is sensitive to the data distribution.
We need to use statistical methods to make statistical inference based on probability models.
High-dimensional statistical inference, variable selection, classification and the related big data problems.
Therefore, we need to use statistical methods to make statistical inference based on probability models.
Statistical inference based on Pearson's correlation coefficient often focuses on one of the following two aims:.
Given a parameter or hypothesis about which one wishes to make inference, statistical inference most often uses:.
More sophisticated statistical inference tools can be used to quantify the likelihood of observing data samples given an assumption.
These inconsistencies can translate intoerroneous analytical results which can skew statistical inferences considerably.
In this talk, I will discuss a general statistical inference problem built on a network structure, with a special application in transportation.
We will then use linear models to represent differences between experimental units andperform statistical inference on these differences.
It covers everything from testing hypotheses, applying statistical inferences, visualizing distributions and drawing conclusions- all while coding in Python and using real world data sets.
But in the 21st century,culture and politics are increasingly pervaded by the automated form of statistical inference called“machine learning.”.
However, data must be collected according to statistical designs, including the application of probability principles,before they can be used for making statistical inference.
They will learn to collect and use data from a variety of sources, including the web,in a modern statistical inference and visualization paradigm.
You should have studied microeconomics(or economic theory, game theory, industrial organisation) and econometrics(or statistics,regression analysis or statistical inference).
Wringing intelligent insights from Big Dataposes formidable challenges for computer science, statistical inference methods and even the scientific method itself.
I think it is much more likely thathuman language learning involves something like probabilistic and statistical inference, but we just don't know yet.
Because of the time lag in data generation, the assessment of progress in attaining the goals and targets--using statistical inference-- will be included in subsequent reports only.