Statistics - Shrub Carbon

This is a follow up to the Scientific Python 7 exercise.

Dr. Granger is interested in studying the factors controlling the size and carbon storage of shrubs. This research is part of a larger area of research trying to understand carbon storage by plants. She has conducted a small preliminary experiment looking at the effect of three different treatments on shrub volume at four different locations. She wants to conduct a preliminary analysis of these data to include in a grant proposal and she would like you to conduct the analysis for her (she might be a world renowned expert in carbon storage in plants, but she sure doesn’t know much about computers). She has placed a data file on the web for you to download. She wants you to run an ANOVA to determine if the different experimental treatments lead to differences in shrub carbon.

1. Import the data using Pandas and print out the first few rows of the data using the .head() method.
2. Write a function to calculate the shrub carbon using a column of lengths, a column of widths and a column of heights, using the equation 1.8 + 2 * log(volume) where volume is the volume of the shrub. You’ll need to use the numpy version of the log() function. Call the function to get a column of shrub carbons and then print out that column.
3. Use this function to get a column of carbons for all of the shrubs in the table and append that column to your existing dataframe using a command like data['carbon'] = get_shrub_carbons(lengths, widths, heights). Print out the entire dataframe.
4. Do an ANOVA to determine if the experiment has an influence on the shrub carbon and print out the results in a standard ANOVA table using anova_lm(). You can import anova_lm() using from statsmodels.stats.anova import anova_lm.