Chapter13_Part1 - Text Part 5 (p. 191) Statistical...

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Text Part 5 (p. 191) Statistical Relationship Between Variables Spatial association (map patterns) Correlation analysis (Ch. 13) Measure of strength of association E.g., income level and crime rates are strongly correlated Regression Analysis (Ch. 14) A known association is used to predict E.g., if we know income level we can predict crime rates
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Chapter 13: Correlation Introduction Correlation Analysis Based on a series of paired measurements The study of association between two variables Spatial: two variables measured at the same location in space. A paired measurement Temporal: two variables measured at the same time.
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Chapter 13: Correlation Paired Measurements Spatial: E.g., each point on the map has a set of paired measurements: Temperature; Elevation. There are 12 pairs in total.
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Chapter 13: Correlation Paired Measurements Temporal: 12 hourly measurements would yield 12 pairs in total. E.g., this weather station logs a set of paired measurements every hour: Temperature; Wind speed.
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Chapter 13: Correlation Correlation Correlation can be represented in two ways: 1. Graphically: Scatter gram or Scatter plot Variable X Variable Y 2. Numerically: Correlation Coefficient -1 to <0: negative correlation 0: no correlation >0 to +1: positive correlation
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Chapter 13: Correlation Correlation Scatterplot (graph) or coefficient (value) reveals: 1. Direction of association 2. Strength of association Positive : both variables increase in magnitude. Negative
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This note was uploaded on 01/18/2011 for the course GEOG 339 taught by Professor Staff during the Fall '10 term at University of Calgary.

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Chapter13_Part1 - Text Part 5 (p. 191) Statistical...

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