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HP 1100 Tutorial for Week 13 Regression [Dataset] “Week13_Nov10_Regression.sav” 1. Regression 1) Scatter Plot : add the fit line 2) Identify the equation : bX a Y ˆ By hand: x SS SP b a Y b X = 5, = 3, SSX = 8, SSY = 32, SP = 11 X X Ȳ b = 11 8 = 1.375 a = 3 1.375 × 5 =− 3.875 ^ Y =− 3.875 + 1.375 X By SPSS: Analyze --> Regression --> Linear 3) Interpret the results : a: the Y-intercept, where the line crosses the Y-axis; a is the average of Y when X = 0. b: the slope, the direction and degree to which the line is tilted; on average speaking, when X changes by 1 unit, b is the amount of change in Y. R **Compare R with the correlation coefficient obtained from Pearson correlation.

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• Fall '16
• cecilia
• Statistics, Nov 10, Correlation and dependence, Pearson product-moment correlation coefficient, Spearman's rank correlation coefficient, Pearson correlation coefficient, 47.3%

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