## Statistics

# Shrub Volume 3

This is a follow up to Shrub Volume 2.

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.

- Import the data using Pandas and print out the first few rows of the data
using the
`.head()`

method.
- 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.
- 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.
- 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
```

.

[click here for output]