POL S 15 Lecture Notes - Lecture 8: Scatter Plot, Dependent And Independent Variables, Observational Error
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Hw #3 due a week from today, peer review due nov. 4. Midterm november 5 - study guide on gauchospace. Wanting to see a pattern on the scatterplot. Pearson"s correlation coefficient is appropriate when we have two interval variables. Closer to 1 (absolute value of either -1 or 1) = stronger correlation. Negative means inverse relationship, positive = direct relationship between independent and dependent variables. The proportion of our variables" variance that is shared. ** the dependent variable changes, so this measures how much or closely that variance goes along with independent variable variance ** So basically seeing how strongly/closely the dependent and independent variables interact. All you do is take the square of the pearson correlation coefficient. Multiply r by itself (r x r) or (r2) The closer to 1, the stronger the relationship. So 41% of the two variables" variance is shared.
