1. Planning your research & types of data
Stats Club 1: Nov 2016
Marnie Brennan

2. How this works…. 2 sessions a month, the same session is run twice
1.5hrs maximum
20-30 min introduction
30 min plus practical time
Fridays
Alternates between 9-10:30am, and 9:30-11am
Bite-sized topics
Informal

3. We are not statisticians!
We know a few things about a few things…..
We can cover the basics, and signpost
If it is complicated, get advice BEFORE you start your study
Low level – build on this
More than one way to skin a stat!
Every day is a school day!

4. References Petrie and Sabin - Medical Statistics at a Glance
Really good for beginners
Petrie and Watson - Statistics for Veterinary and Animal Science
This is the standard textbook for undergrads, is very useful
Thrusfield – Veterinary Epidemiology
Good for general concepts
Kirkwood and Sterne – Essential Medical Statistics
Can have out of the ordinary stuff
Dohoo, Martin and Stryhn – Veterinary Epidemiologic Research
This is hard core!

5. References recommended by others
“Experimental Design for the Life Sciences” by Graeme Ruxton
“Statistics explained, an introductory guide for life scientists” by Steve McKillup
“Modern statistics for the life sciences” by Alan Grafen and Rosie Hails
“Experimental design and data analysis for biologists” by Gerry P. Quinn and Michael J. Keough

6. Statistical packages we know!
University software we commonly use:
Minitab
SPSS (PASW)
Genstat
Vet School software:
Simca
There are people in the vet school who use:
R (Free software)
Stata
MLwiN (Free software to academics)

7. References for today
Petrie and Sabin - Medical Statistics at a Glance: Chapter 1
Petrie and Watson - Statistics for Veterinary and Animal Science: Chapter 1
‘Experimental design for Science and Engineering’ resource on the Workspace page

8. Planning your research
It all begins with an aim….
Hypothesis driven versus exploratory studies
Determines what data you collect
And therefore how you analyse it
Don’t underestimate the power of descriptive statistics!
Seems simple, but remember to do it!

9. Planning your research
Logistics
The 5 P’s
Prior Preparation Prevents Poor Performance!
Statistics cannot fix a badly designed experiment
Poorly collected data = Poor conclusions

10. Planning your research
Logistics
Factor in timing for planning and training
When are you starting your data collection?
Make sure you know what type of data you will have BEFORE you start to collect anything
Make sure you know what ANALYSIS you will do with it before you collect it
This will assist you in optimising the best way to RECORD it for analysis
When might you need help?
Factor in statistics training into your planning
Organise help at the beginning (no surprises!)
It is easy to identify ‘rushed jobs’
The usefulness of your research will be poorer if you don’t

11. An example
Age
If you were conducting a survey, and wanted to ask people’s age, how would you ask the question?
Please enter you age in years
Please tick the box which is relevant to your age in years
Under 25
Between 25 and 34
Between 35 and 44
45 or over
Which is better?

12. Types of data Two main types of data: Numerical Categorical
Data has a numerical value
e.g. weight, height, number of visits to the vet in a 12 month period
Categorical
Data can only be classified into a distinct number of categories
e.g. sex (2 categories), neuter status (4 categories), disease status (mild, moderate, severe – 3 categories)

13. Types of data Numerical Can subdivide into 2 categories Discrete data
Concerns whole numbers e.g. number of visits to the vet in the past 12 months
Often counts of events
Continuous data
Does not have to be whole numbers e.g. weight in grams (53.5gms) or kilograms (1.2 kg)

14. Types of data Numerical Weight (kg) Number of vet visits 4.4 1 4.5 2
6.1
5.0
6.0
5.6 5
3.1 8
4.8 3
5.7
6.3 4

15. Types of data Categorical Can subdivide into 2 different categories
Ordinal
The categories have an order to them e.g. 3 categories of disease – mild, moderate or severe
Nominal
Categories, but not ordered e.g. neuter status (Male Entire, Male Neuter, Female Entire, Female Neuter)

16. Types of data Categorical Disease severity Neuter status 1 2 3 4
1=Mild
1=ME
2=Moderate
2=MN
3-Severe
3=FE
4=FN

17. Think about your own research – what data do you have/will you have?
Your turn!
Think about your own research – what data do you have/will you have?

18. Exercises
Work in pairs – what types of data do you think are involved in the following scenarios?

19. Look at the abstract below, and the data in the accompanying Excel document (called Exercise 2) – what type of data is in Column I?
PLoS ONE (2013) 8:8

20. Look at the primary outcome of interest in this study – what type of data is it?

21. Look at the graph below and determine what type of data it is
Data representing the number of dog attacks in NSW, Australia

22. Preventive Veterinary Medicine (2003) 60: 307-317
Look at the abstract below and determine what type of data the primary outcome is
Preventive Veterinary Medicine (2003) 60:

23. What type of data is being used to measure sedation in this study?
Journal of Feline Medicine and Surgery (2006) 8: 15-21

24. Type of study design
The type of data you will get is also dependent on the type of study design that is used
Important to be familiar with these!
Cross-sectional studies
Case-control studies
Cohort studies
Randomised controlled trials
E.g. Cross-sectional survey or questionnaire – likely to have categorical data
Suggested textbooks

25. Next month
Data entry and preparation for analysis