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Fieldwork - Coggle Diagram
Fieldwork
Planning
Inquiry/Question + Hypothesis (Know what you're looking for)
Risk Assessment + Method Planning (What data are you going to collect? How are you going to collect it?)
Recording (How are you going to record your data?)
Analyse and Conclude (Does this answer your question? What are the statistics?)
Evaluate (Is it reliable? What would you do differently next time? What went well?)
Data Presentation
Graphs and charts (Line, scatter, bar, pie, etc)
Tables, tallies, and lists
Illustrations and mindmaps
Techniques
Continuous Data - Show a change in data along a line of study or over a period of time
Categories - Shows classifications to determine the data being presented
Locations - Where your data is different, locate data on maps/aerial photos for easy presentation
Evaluation and Analysis
T - Trend/Pattern (What is the pattern? Is there a pattern?)
E - Explain (What reasons are there for your findings? Who could give different answers? Could your answers change?)
A -Anomalies (Any strange results? Anything that breaks the pattern?)
Sources of Error
Sample size (Small size Usually means lower quality of data)
Frequency of sampling (Fewer sites reduces frequency)
Type of sampling (May create "gaps" and introduce bias)
Equipment used (Wrong/Inaccurate equiptment can affect quality)
Time of survey (Different times can significantly influence factors)
Location of survey (Different locations can significantly influence factors)
Quality of secondary data (Age and reliability can affect overall quality)
Primary Vs Secondary
Primary Data - Data that has been collected firsthand
Things to consider while collecting primary data
Sample Size (What measurements/data will you be taking? How many/much measurements/data will you be taking?)
Locations/Sites (Where will you collect this data? Does locations matter? Is it biased?)
Accuracy (How can you ensure that this data is accurate? Can it be accurate? How can you prove that?)
Secondary Data - Data that has been collected by someone else
Quantitative Vs Qualitative
Quantitative Data - Data than records quantities (E.g numbers, sizes, or frequencies)
Random - Samples are collected/chosen at random
Systermatic - Samples are collected/chosen in a system/pattern
Stratified - Samples are collect/chosen by deliberately introducing bias to ensure variety of results for fair approach
Techniques
Median - Order the data in order of size from smallest to largets and determine the middle value
Mode - The number that appears the more frequently in the data set
Range - The difference between the highest and lowest values in the data set
Quatiles - Dividing a list of numbers into four equal groups (Two above and two below the median)
Qualitative Data - Data that records subjective qualities (E.g opinions, attitudes, and beliefs)
Data Collection
Examples: Questionnaires, land use surveys, residential housing survey, pedestrian/traffic counts, retail diversity survey, air quality and noise measurements, car park survey, etc