Examples of using Hypothesis testing in English and their translations into Serbian
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Cyrillic
You will also learn hypothesis testing.
Hypothesis testing, probability and confidence interval.
Hypothesis testing for engineering aspects of forensic cases.
Statistical hypothesis testing.
Some people can call it rapid experimentation, but more importantly,we call it‘hypothesis testing.'.
Categories: Hypothesis Testing, Optimization.
Parametric and nonparametric hypothesis testing.
Now when you do a hypothesis testing, there can be two types of errors.
Researchers running fully factorial experiments will need to be concerned about multiple hypothesis testing;
Multivariate statistics libraries including fitting, hypothesis testing, and probability and expectation calculations on over 160 distributions.
Often this results from investigating too many hypotheses andnot performing proper statistical hypothesis testing.
The Analyse phase uses statistical analysis and hypothesis testing to model how processes may be improved and the potential value of each.
Hypothesis testing: assuming a possible explanation to the problem and trying to prove(or, in some contexts, disprove) the assumption.
Research should be accrued in the same manner as the scientific method,using observation, hypothesis, testing, data, analysis and generalization.
His emphasis on hypothesis testing helped change ecology from a primarily descriptive field into an experimental field, and drove the development of theoretical ecology.
This view gave rise tothe term processual archaeology. Processualists borrowed from the exact sciences the idea of hypothesis testing and the scientific method.
The Analyse Phase: Use statistical analysis and hypothesis testing to model how processes may be improved and the potential value of each improvement.
Specifically, students will be exposed to the concepts of statistical inference, probability, probability distribution, sampling distribution,estimation, and hypothesis testing.
The Analyse phase uses statistical analysis and hypothesis testing to model how processes may be improved and the potential value of each improvement without affecting existing systems.
To me, being able to come up with the new ways of doing things, new ways of framing what is a failure and what is a success, how does one achieve success--it's througha series of failures, a series of hypothesis testing.
While introductory textbooks may introduce degrees of freedom as distribution parameters or through hypothesis testing, it is the underlying geometry that defines degrees of freedom, and is critical to a proper understanding of the concept.
The new methodological approaches of the processual research paradigm include logical positivism(the idea that all aspects of culture are accessible through the material record), the use of quantitative data, andthe hypothetico-deductive model(scientific method of observation and hypothesis testing).
The new one calls science“a systematic method of continuing investigation that uses observation, hypothesis testing, measurement, experimentation, logical argument and theory building to lead to more adequate explanations of natural phenomena.”.
These inferences may take the form of:answering yes/no questions about the data(hypothesis testing), estimating numerical characteristics of the data(estimation), describing associations within the data(correlation) and modeling relationships within the data(for example, using regression analysis).
Topics are types of data, location and variability measures, samples and populations, distributions,confidence intervals, hypothesis testing, comparing two or more means or proportions(parametric and non-parametric methods), and relationships between two variables(correlation, simple linear regression).
We will discuss and utilize location and variability measures, samples and populations, distributions,confidence intervals, hypothesis testing, comparisons between two or more means or proportions(parametric and non-parametric methods), and relationships between two variables(correlation and simple linear regression).
At the same time, this course enables students to understand the principles of statistics, the notion of probability, random variable, statistical estimation,as well as statistical hypotheses testing, and regression and correlation analysis for random variables.
Estimate of parameters and testing hypothesis.
Estimate of parameters and testing hypothesis.