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MCDW data is recommended as a data source by libraries and other information providers, such as the University of Chicago Library. [3] Other publications, including annual regional climate data publications, have also cited and used MCDW data. [4] Academic research in meteorology has often cited MCDW data. [5] [6] [7]
The following is a bottom-line analysis table from the various monthly stats pages. The table below assesses all hooks from 2024; data are also available for imaged hooks and non-imaged hooks in this year.
Data and information visualization; Data point; Datasaurus dozen; Defect concentration diagram; Dendrogram; Distribution-free control chart; DOE mean plot; Dot plot (bioinformatics) Dot plot (statistics) Double mass analysis; Dual-flashlight plot
Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series.It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components.
Completeness (statistics) Compositional data; Composite bar chart; Compound Poisson distribution; Compound Poisson process; Compound probability distribution; Computational formula for the variance; Computational learning theory; Computational statistics; Computer experiment; Computer-assisted survey information collection; Concomitant (statistics)
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2008 October – Multilingual statistics – monthly details of total article count, and analysis of the monthly rate of article growth, for each version of Wikipedia. 2008 May – Most frequently edited pages – Updated based on data as of 23 May 2008.
A trend exists when there is a persistent increasing or decreasing direction in the data. The trend component does not have to be linear. [1], the cyclical component at time t, which reflects repeated but non-periodic fluctuations. The duration of these fluctuations depend on the nature of the time series.