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  2. Could you pass GCSE maths? Take our quiz to test your ... - AOL

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  3. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A histogram is a representation of tabulated frequencies, shown as adjacent rectangles or squares (in some of situations), erected over discrete intervals (bins), with an area proportional to the frequency of the observations in the interval. The height of a rectangle is also equal to the frequency density of the interval, i.e., the frequency ...

  4. Additional Mathematics - Wikipedia

    en.wikipedia.org/wiki/Additional_Mathematics

    Format for Additional Mathematics Exam based on the Malaysia Certificate of Education is as follows: Paper 1 (Duration: 2 Hours): Questions are categorised into Sections A and B and are tested based on the student's knowledge to grasp the concepts and formulae learned during their 2 years of learning. Section A consists of 12 questions in which ...

  5. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    The total area of a histogram used for probability density is always normalized to 1. If the length of the intervals on the x-axis are all 1, then a histogram is identical to a relative frequency plot. Histograms are sometimes confused with bar charts. In a histogram, each bin is for a different range of values, so altogether the histogram ...

  6. Cumulative frequency analysis - Wikipedia

    en.wikipedia.org/wiki/Cumulative_frequency_analysis

    Histogram derived from the adapted cumulative probability distribution Histogram and probability density function, derived from the cumulative probability distribution, for a logistic distribution. The observed data can be arranged in classes or groups with serial number k. Each group has a lower limit (L k) and an upper limit (U k).

  7. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    This histogram provides an estimate of the shape of the distribution of the sample mean from which we can answer questions about how much the mean varies across samples. (The method here, described for the mean, can be applied to almost any other statistic or estimator .)

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