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Part 4: Data Recording, analysis & presentation (Mathematical skills…
Part 4: Data Recording, analysis & presentation
Raw Data
Raw data hasn't been processed/analysed in any way. (e.g. list of all of your pp's individual scores)
Most common way to present raw data is in a raw data table. Simple table with your pp's raw scores. When collecting raw data in an experiment your raw data table split in two columns, one for each condition.
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Mathematical skills
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- Make estimations from data collected
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Measures of dispersion
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Variance- 1. Work out mean.
- Then for each number: subtract mean and square result.
- Add all scores together.
- Divide by number of scores -1.
Standard Deviation- Work out variance and calculate square root. More precise calculations of distribution less affected by anomalous results. More difficult to calculate than range.
Frequency tables
Used to display how often event occurred. E.g. how many times pp's displayed range of behaviours when waiting at a bus stop.
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Histogram
Similar to bar chart except for continuous data. Vertical axis must start at 0 and horizontal axis must be continuous, no gaps.
Bar chart
Summary of data. Height of each bar represents frequency of each item. Gaps between bars show not continuous. Bar chart good for showing means in 2 conditions or frequency of behaviour in observation.
Line Graph
Histogram, continuous data on x-axis. Dot marked at top of bar and line connects dots. Allow 2 sets of data to be displayed.
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Scatter diagram
Graph display correlational data. Shows whether positive, negative or no correlation been found.
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