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Independent Analysis Project

Independent Analysis Project. Data Screening - Due April 10 ( 5 points). Instructions: Submit one file by email to khyrenba@gmail.com A ppt file with your name as suffix (e.g., MARS6300_DataScreening_KDH.ppt) containing PC-ORD output text and figures.

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Independent Analysis Project

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  1. Independent Analysis Project • Data Screening - Due April 10 ( 5 points) Instructions: Submit one file by email to khyrenba@gmail.com A ppt file with your name as suffix (e.g., MARS6300_DataScreening_KDH.ppt) containing PC-ORD output text and figures

  2. Screening #1 – Data Summary (2 points) • Provide a summary of the data sets you will use in your project, making sure you explicitly discuss: • How many species / variables selected for analysis ? • What criteria did you use to make this selection ? • How many environmental variables used ? Are they Q / C ? • Summarize environmental variables (skewness) (use PC ORD) • Summarize species data (skewness) (use PC ORD) • Perform outlier analysis for species / samples (use PC ORD) • Summarize sums / ranges for species / variables (use PC ORD) • Summarize “zero” data; “empty” species / samples (use PC ORD) • Report species dominance (plot / table) – if you have species data

  3. Screening #2 – Data Transformations (2 points) • Provide a summary of the data transformations you will do, making sure you explicitly explain: • Which transformations you propose to do and why . Hint: use PC-ORD to identify outliers and to summarize descriptive statistics? • Changes in Environmental variable skewness after transformation • Changes in Species data skewness after transformation • Perform outlier analysis again for species and samples after transformations, to see if they solved problems identified above

  4. Screening #3 – Cross-Correlations (1 point) • Provide a summary of the data cross-correlations, making sure you report the following: • Cross-correlations of environmental variables (r and p values) • Plot scatterplots of environmental variables (use PC-ORD) • Brief narrative explaining what these cross-correlations show

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