Phân tích số liệu bằng phần mềm r phần 5

1 Give a man three weapons – correlation, regression and a pen – and he will use all three (Anon, 1978) 2 Ví dụ Tuổi và hàm lượng cholesterol Trong 18 cá nhân nghiên cứu ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Age Chol (mg/ml) 46 3.5 20 1.9 52 4.0 30 2.6 57 4.5 25 3.0 28 2.9 36 3.8 22 2.1 43 3.8 57 4.1 33 3.0 22 2.5 63 4.6 40 3.2 48 4.2 28 2.3 49 4.0 3 1 Nhập dữ liệu trong R id [...]... another measure of strength of association An r = 0.7 may sound impressive, but R2 is 0.49!  Correlation does not mean causation 47 Some comments: Interpretation of correlation  Be careful with multiple correlations For p variables, there are p(p – 1)/2 possible pairs of correlation, and false positive is a problem  Correlation can not be inferred directly from association  r( age, weight) = 0. 05; r( weight,... 30 35 b mi 46 Some comments: Interpretation of correlation  Correlation lies between –1 and +1 A very small correlation does not mean that no linear association between the two variables The relationship may be non-linear  For curlinearity, a rank correlation is better than the Pearson’s correlation  A small correlation (eg 0.1) may be statistically significant, but clinically unimportant  R2 is... phần dư đóng vai trò quan trọng trong tất cả các quy trình phân tích 33 11 Kiểm tra giả thiết  Kiểm tra về phương sai (constant)  Plot the studentized residuals versus their predicted values Examine whether the variability between residuals remains relatively constant across the range of fitted values  Assumption of normality  Plot the residuals versus their expected values under normality (Normal... 26 .50 , 35. 50, 4.0, 5. 4, 3 .5, 2.0, 1 .5, 6.3, 3.7, 2.1, 41 Linear regression analysis of BMI and SA reg |t|) (Intercept) 4.9 251 2 0.64489 7.637 1.81e-09 *** bmi -0. 059 67 0.02862 -2.084 0.0432 * Signif codes: 0 '***' 0.001 '**' 0.01 '*' 0. 05 '.' 0.1 ' ' 1 Residual... 8 0 5 1 6 0 Standardized residuals 1.0 17 -1 6 0 .5 Standardized residuals 1 .5 2 .5 2 0.0 Cook's distance 2 .5 3.0 3 .5 4.0 4 .5 0.00 0. 05 Fitted values 0.10 0 5 0. 15 0.20 Leverage 0. 25 40 A non-linear illustration: BMI and sexual attractiveness  Study on 44 university students  Measure body mass index (BMI)  Sexual attractiveness (SA) score id ...  Be careful with multiple correlations For p variables, there are p(p – 1)/2 possible pairs of correlation, and false positive is a problem  Correlation can not be inferred directly from association... 23.00, 26 .50 , 35. 50, 4.0, 5. 4, 3 .5, 2.0, 1 .5, 6.3, 3.7, 2.1, 41 Linear regression analysis of BMI and SA reg