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  2. Margin of error - Wikipedia

    en.wikipedia.org/wiki/Margin_of_error

    For a confidence level, there is a corresponding confidence interval about the mean , that is, the interval [, +] within which values of should fall with probability . ...

  3. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

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  5. PS Power and Sample Size - Wikipedia

    en.wikipedia.org/wiki/PS_Power_and_Sample_Size

    Matched or independent study designs may be used. Power, sample size, and the detectable alternative hypothesis are interrelated. The user specifies any two of these three quantities and the program derives the third. A description of each calculation, written in English, is generated and may be copied into the user's documents.

  6. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    The sample data is a random sampling from a fixed distribution or population where every collection of members of the population of the given sample size has an equal probability of selection. Variants of the test have been developed for complex samples, such as where the data is weighted. Other forms can be used such as purposive sampling. [8]

  7. I'm an Uber product manager who uses AI to automate ... - AOL

    www.aol.com/news/im-uber-product-manager-uses...

    Nimisha Sharath, a product manager at Uber, says she uses AI to automate about 30% of her job.. She estimates AI saves her up to 100 minutes a day on meeting follow-up. She says AI helps her focus ...

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  9. Quantification of margins and uncertainties - Wikipedia

    en.wikipedia.org/wiki/Quantification_of_margins...

    Quantification of Margins and Uncertainty (QMU) is a decision support methodology for complex technical decisions. QMU focuses on the identification, characterization, and analysis of performance thresholds and their associated margins for engineering systems that are evaluated under conditions of uncertainty, particularly when portions of those results are generated using computational ...

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