1. LEM4001
Analysing your Data

2. The research cycle

3. How do you intend to analyse your data?
Key questions
For your own thesis, what is your proposed experimental design and sampling effort?
How do you intend to analyse your data?

4. For revision purposes…...
Dytham, C. (2011) Choosing and Using Statistics: a Biologist’s Guide. Wiley- Blackwell. Van Emden, H. (2008) Statistics for Terrified Biologists. Blackwell Publishing. Statistics hell:

5. Task : Review the student datasets for:
Resistant blackgrass in winter wheat: an assessment of current chemical controls and potential new chemistry. OR
Habitat preferences of bats at the Upton development, Northampton
Relationship between the horse chestnut bleeding canker pathogen and tree physical diagnostics.
On your own or in pairs now attempt to analyse the data. Graph paper and calculators are available, as are laptops. Review the guides to Minitab and MS Excel and use this software if you wish.

6. Choosing the right test
For the data you evaluated, suggest some suitable statistical tests. Are you all in agreement?
Now do the same for your own proposed thesis and share your ideas with your neighbour.
How will your proposed experimental design and sampling effort influence your choice of statistical test?

7. Inferential statistics
Context
Parametric
Non-parametric
Frequency data testing whether observed data differs from what is expected
Chi-square
Unpaired data of replicate values for two treatments, e.g.: statistical test results
t-test
Mann Whitney Test or Kolmorgorov-Smirnov two sample test
Paired data of replicate values for two treatments
Paired t-test
Wilcoxons signed rank test
Analysis of more than two replicated treatments
Analysis of Variance (ANOVA)
Kruskal Wallis analysis of ranks
Correlation of two variables
Pearson Correlation
Spearman Rank Correlation
Modelling the association of a dependent variable on an independent variable
Linear regression
Transform data to normality – then linear regression
Modelling the association of dependent variables on more than one independent variable
Two way ANOVA or General Linear Model (GLM)
Friedman Two Way Analysis

8. Menu…..?
MENU Starter Descriptive Statistics Mains Inferential Statistical Tests Probability Using Minitab, R and MS Excel in Quantitative Analysis Dessert Multi-variate Statistics

9. Use of Minitab for statistical analysis
Review Minitab v. 3.1 guide.
Use Minitab to interpret the class data or process the example data on the worksheet. If you require the class data, this is held on an MS Excel spreadsheet on Moodle.
Interpret your data using:
i. Descriptive statistics.
ii. Basic tests for associations or differences.
Q. Difficulties?
Homework: Work your way through the Minitab guide.
Next time: Using Minitab for more advanced tests (including linear regression analyses and GLM’s).

10. sources of further reading
Rowntree, D. (1981) Statistics without Tears. Penguin. ‘Ready to Research’ Quantitative Analysis portal: research-methods Handbook of biological statistics: UoN Skills Hub > Essential Tools > Data Analysis: