3 datasets found
  1. Statistical Data Analysis using R

    • figshare.com
    txt
    Updated May 30, 2023
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    Samuel Barsanelli Costa (2023). Statistical Data Analysis using R [Dataset]. http://doi.org/10.6084/m9.figshare.5501035.v1
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    txtAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Samuel Barsanelli Costa
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    R Scripts contain statistical data analisys for streamflow and sediment data, including Flow Duration Curves, Double Mass Analysis, Nonlinear Regression Analysis for Suspended Sediment Rating Curves, Stationarity Tests and include several plots.

  2. R Code for plotting statistical parameters of Nd and Sr isotopic signature...

    • figshare.com
    txt
    Updated Jun 1, 2023
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    Cecile Blanchet (2023). R Code for plotting statistical parameters of Nd and Sr isotopic signature of Potential Source Areas [Dataset]. http://doi.org/10.6084/m9.figshare.6990260.v4
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    txtAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Cecile Blanchet
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This code permits to plot box and whiskers plots to evaluate the statistical distribution of radiogenic Neodymium and Strontium isotope values. The particular application is to fingerprint Potential Source Areas for dust generation in North Africa.

  3. Data from: Determination of the optimum plot size for tomato seedlings

    • scielo.figshare.com
    xls
    Updated Jun 1, 2023
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    Jeniffer Ribeiro de Oliveira; Weslley do Rosário Santana; Mayara Nascimento Santos; Edilson Romais Schmildt (2023). Determination of the optimum plot size for tomato seedlings [Dataset]. http://doi.org/10.6084/m9.figshare.19929208.v1
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELOhttp://www.scielo.org/
    Authors
    Jeniffer Ribeiro de Oliveira; Weslley do Rosário Santana; Mayara Nascimento Santos; Edilson Romais Schmildt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ABSTRACT The objectives of this work were to determine the optimum plot size for tomato seedlings by Hatheway’s method, using the Mestiço and Ozone cultivars, and verify the possibility to obtain the optimum plot size only by non-destructive characteristics. Non-destructives (aerial part height, stem diameter, number of leaves and leaf area) and destructives (aerial part dry matter, root dry matter, total dry matter and Dickson quality index) characteristics were evaluated. For each characteristic evaluated, experimental plans were simulated in a randomized block design with the combination of I treatments (I = 3, 4, 5, ..., 10, 15, 20 and 25) and R repetitions (R= 3, 4, 5, 6 and 7). The optimum plot size ranged according to the characteristic evaluated. Considering the number of treatments, repetitions and the same experimental accuracy, the stem diameter showed the highest size plot. Thus, the stem diameter can be used as a basis characteristic for the non-destructives characteristics, without the need to destroy the seedling.

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Samuel Barsanelli Costa (2023). Statistical Data Analysis using R [Dataset]. http://doi.org/10.6084/m9.figshare.5501035.v1
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Statistical Data Analysis using R

Explore at:
54 scholarly articles cite this dataset (View in Google Scholar)
txtAvailable download formats
Dataset updated
May 30, 2023
Dataset provided by
figshare
Figsharehttp://figshare.com/
Authors
Samuel Barsanelli Costa
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

R Scripts contain statistical data analisys for streamflow and sediment data, including Flow Duration Curves, Double Mass Analysis, Nonlinear Regression Analysis for Suspended Sediment Rating Curves, Stationarity Tests and include several plots.

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