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  2. Five-number summary - Wikipedia

    en.wikipedia.org/wiki/Five-number_summary

    The five-number summary is a set of descriptive statistics that provides information about a dataset. It consists of the five most important sample percentiles: the sample minimum (smallest observation) the lower quartile or first quartile; the median (the middle value) the upper quartile or third quartile; the sample maximum (largest observation)

  3. Influential observation - Wikipedia

    en.wikipedia.org/wiki/Influential_observation

    In statistics, an influential observation is an observation for a statistical calculation whose deletion from the dataset would noticeably change the result of the calculation. [1] In particular, in regression analysis an influential observation is one whose deletion has a large effect on the parameter estimates.

  4. Estimation statistics - Wikipedia

    en.wikipedia.org/wiki/Estimation_statistics

    Estimation statistics, or simply estimation, is a data analysis framework that uses a combination of effect sizes, confidence intervals, precision planning, and meta-analysis to plan experiments, analyze data and interpret results. [1]

  5. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    For B = 10% one requires n = 100, for B = 5% one needs n = 400, for B = 3% the requirement approximates to n = 1000, while for B = 1% a sample size of n = 10000 is required. These numbers are quoted often in news reports of opinion polls and other sample surveys. However, the results reported may not be the exact value as numbers are preferably ...

  6. Summary statistics - Wikipedia

    en.wikipedia.org/wiki/Summary_statistics

    In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Statisticians commonly try to describe the observations in

  7. Sample mean and covariance - Wikipedia

    en.wikipedia.org/wiki/Sample_mean_and_covariance

    The sample mean and sample covariance are not robust statistics, meaning that they are sensitive to outliers. As robustness is often a desired trait, particularly in real-world applications, robust alternatives may prove desirable, notably quantile-based statistics such as the sample median for location, [4] and interquartile range (IQR) for ...

  8. Statistical assumption - Wikipedia

    en.wikipedia.org/wiki/Statistical_assumption

    These relate to the way observations have been gathered, and often involve an assumption of randomization during sampling. [ 6 ] [ 7 ] The model-based approach is the most commonly used in statistical inference; the design-based approach is used mainly with survey sampling .

  9. Sample maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Sample_maximum_and_minimum

    In statistics, the sample maximum and sample minimum, also called the largest observation and smallest observation, are the values of the greatest and least elements of a sample. [1] They are basic summary statistics , used in descriptive statistics such as the five-number summary and Bowley's seven-figure summary and the associated box plot .