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Week 4 Study Notes

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Damian Dupuy
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GGR 270 โ€“ Lecture 4 โ€“ October 6, 2010
Normal Distribution โ€“ Z Scores
๎€Standard scores are referred to as Z Scores
๎€Indicate how many Standard Deviations separate a particular value from the mean
๎€Z Scores can be positive or negative depending if they are > or < the mean
๎€Z score of the mean is O and the Standard Deviation is positive or negative
๎€Table of normal values provides probability info on a standardized scale
๎€But, we can also calculate Z scores
๎€Formula involves comparing values to the mean value, and dividing by the Standard
Expressed as:
๎€Result is interpreted as the โ€˜number of standard deviations an observation lays above
or below the meanโ€™.
๎€Measures the degree of symmetry in a frequency distribution
๎€Determines how evenly the values are distributed either side of the mean
Expressed as:
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Coefficient of variation
๎€Allows for comparison of variability of spatial samples
๎€Tests which sample has the greatest variability
๎€Standard deviation or variance are absolute measures, so they are influenced by the
size of the values in the dataset
๎€To allow a comparison of variation across 2 or more geographic samples, can use a
relative measure of dispersion called coefficient of variation
Expressed as:
Describing Bivariate data
๎€Comparative pie-charts
๎€Stacked bar chart
๎€Allows us to observe statistically the relationship between 2 variables
๎€Looking at the strength and direction of the relationship between 2 variables
๎€Most common graphing technique is the scatter plot
Direction of the Bivariate relationship
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