ASSESSMENT:
The aim of this assessment is for you to demonstrate that you are able to independently analyse a dataset you have gathered in R. Remember to differentiate between ‘treatments’, ‘independent samples’ and ‘replicates’ when choosing data for analysis (refer to first lecture and reading).
Note both Excel and Text files have been provided with your data, these files may not be in the correct format for appropriate analysis and you may want to carry out further refinement. If you choose to do this, save your edited Excel files as a text file to be imported into R (make sure the column names are sensible).
As part of this assessment you are expected to:
1. Develop two sets of hypothesis (each with both a null [H0] and alternate [H1]) which consider physical
or chemical differences between the top and sub soil.
2. Provide a set of descriptive statistics for each variable measured for both top and sub soil. This information must be provided in a table and the R code used to achieve this table must be listed beneath.
3. Provide a graph (export from R and insert into your document) which summarises the data used to test each hypothesis, also list the code used to generate the graph.
4. Test the appropriate data for normality; present the output and your interpretation.
5. Select and run an appropriate inferential test for each hypothesis. You must provide evidence for inferential test outputs (code, graphs and test outputs). Provide a short explanation of the process you used to choose the statistical test, i.e explain how your data fulfilled test assumptions (up to 350 words). HINT: Use lecture materials (most of the clues you will need will be available there) with independent reading and research to support this section.
6. State whether the null hypothesis have been accepted or rejected.
