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The log-normal distribution is not an appropriate parametric model for shot length distributions of Hollywood films

机译:对数正态分布不是好莱坞电影镜头长度分布的合适参数模型

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We examine the assertion that the two-parameter log-normal distribution is an appropriate parametric model for the shot length distributions of Hollywood films. A review of the claims made in favour of assuming log-normality for shot length distributions finds them to be lacking in methodological detail and statistical rigour. We find there is no supporting evidence to justify the assumption of log-normality in general for shot length distributions. In order to test this assumption, we examined a total of 134 Hollywood films from 1935 to 2005, inclusive, to determine goodness-of-fit of a normal distribution to log-transformed shot lengths of these films using four separate measures: the ratio of the geometric mean to the median; the ratio of the shape factor sigma to the estimator sigma(star) = root(2 x ln ((x) over bar /M)); the Shapiro-Francia test; and the Jarque-Bera test. Normal probability plots were also used for visual inspection of the data. The results show that, while a small number of films are well modelled by a log-normal distribution, this is not the case for the overwhelming majority of films tested (125 out of 134). Therefore, we conclude there is no justification for claiming the log-normal distribution is an adequate parametric model of shot length data for Hollywood films and recommend the use of robust statistics that do not require underlying parametric models for the analysis of film style.
机译:我们研究了双参数对数正态分布是好莱坞电影镜头长度分布的合适参数模型的断言。对赞成假设注射长度分布的对数正态性的主张进行审查后发现,这些主张缺乏方法细节和统计严谨性。我们发现没有支持证据来证明对数正态性假设的对数正态性对于注射长度分布。为了验证这一假设,我们检查了 1935 年至 2005 年(含)的 134 部好莱坞电影,以确定这些电影的对数变换镜头长度的正态分布拟合优度:几何平均值与中位数的比率;形状因子 sigma 与估计量 sigma(star) 的比值 = root(2 x ln ((x) over bar /M));夏皮罗-弗朗西亚试验;和 Jarque-Bera 测试。正态概率图也用于数据的目视检查。结果表明,虽然少数电影通过对数正态分布很好地建模,但对于绝大多数测试的电影(134 部电影中的 125 部)来说,情况并非如此。因此,我们得出结论,没有理由声称对数正态分布是好莱坞电影镜头长度数据的适当参数模型,并建议使用不需要基础参数模型来分析电影风格的稳健统计数据。

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