This document outlines the planning process for an investigation, including identifying testable hypotheses, determining what data needs to be collected, choosing appropriate sampling locations and methods, assessing risks, and using technology to aid the planning. Some examples of SMART and testable hypotheses are provided. The stages of planning involve forming hypotheses, determining what to measure and sample, considering logistics of locations and timings, and managing risks.
3. SMART
Simple
Measurable
Achievable
Realistic
Timed
LOCATED
4. Which of these are SMART enough to
test? How could you improve them?
River valleys increase in width with
increasing distance from the source
Golf courses in Bucks are located in urban
areas
Do Waitrose source their food from local
suppliers?
Are population densities greater in West or
East Berkshire?
5. Testable Hypothesis
Measurable hypothesis are needed in
order to statistically test your theory
Null Hypothesis
There is no relationship
Hypothesis
There is some form of relationship
10. What do you need to plan?
Hypotheses and
Questions
Risks Types of data
Timings
Sampling
Location
11. Choosing location and sites
Health and Safety?
Appropriate to Key Concepts
Fit in with hypotheses
Accessibility
Time taken to reach them?
Are you doing a PILOT STUDY?
9
12. Types of Data
Primary Data Secondary Data
Raw Data collected Published data that has
either personally or un- been processed,
analysed official data ordered and analysed
Discharge Text books
Rainfall Maps
Census Charts
Electoral register Diagrams
Parish register Journal/ Magazine
Articles
Soil pH
Vegetation data
Landuse data
13. Sampling
Large sample size = more representative data
Point Sampling
Areal Sampling
Linear Sampling
Random
Stratified
Systematic