PSCI 2702 Study Guide - Final Guide: Chi-Squared Test, Null Hypothesis, Regression Analysis

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Y = score on dependent variable a = y-intercept (where x is zero) = the slope (change over x-amount) x = score on independent variable: for slope, when you have a higher slope, there is a strong association. With a lower slope value, you have a weak association: both slope and y-intercept are expressed in the units of the dependent variable, the correlation coefficient (pearson"s r) measures the association between interval-ratio variables. From spss: y=827. 96 + 12869. 103x, 8276. 96- found in coefficients table under constant b, this means that the average income is. Multiple regression analysis: y= a + b1x1 + b2x2 + bnxn. A = y-intercept (where x is zero) B1 = the partial slope of the linear relationship between the first independent variable and y. The portion of variance in y- that is explained by all the independent variables combined, or in other words how all the dependent variables on the dependent variable (combined is the key word here)

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