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But the study, and the New York Times' reporting, uses a small sample of data that leads to simplistic conclusions.
In this case, it is the presentation layout of the data that leads to a productive solution.
The power is the probability, according to the alternative hypothesis $h'$, of obtaining data that leads us to correctly reject the null hypothesis $h$: \[ \text{Power}_{F} = 1 - \beta = P_{h'}(F_{1}) = \sum_{s \in S} F s) P_{h'}(s) d s. \] The probability $\beta$ is called the type-II error of falsely accepting the null hypothesis.
The significance is the probability, according to the null hypothesis $h$, of obtaining data that leads us to falsely reject this hypothesis $h$: \[ \text{Significance}_{F} = \alpha = P_{h}(R_{r}) = \sum_{s \in S} F s) P_{h}(s) d s, \] The probability $\alpha$ is alternatively called the type-I error, and it is often denoted as the significance or the p-value.
It is quite important to do so because it is the raw data that leads to Figure 3C.
It is often the complexity of the data and the difficulty in integrating the data that leads to uncertainty.
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It was that data that led to this week's exchange.
"And the historical data that led me to that conclusion is rock solid".
Yahoo had turned over data that led to the imprisonment of several Chinese activists.
Among the problems, network executives blamed the service for providing flawed exit poll data that led them to call Florida initially for Al Gore.
Dr. Mary Barton, scientific director for the group, said "it is more than just a lack of data" that led to that conclusion.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com