Pp Regresi. Jadippt

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Pp Regresi. Jadippt

  1. 1. REGRESI KELOMPOK 4: ARMAN FERNANDO. S DETTI APRIANI ENI INDRIATI
  2. 2. DEFINISI REGRESI <ul><li># Menurut Sir Francis Galton (1822-1911) Persamaan Regresi :Persamaan matematik yang memungkinkan peramalan nilai suatu peubah takbebas ( dependent variable ) dari nilai peubah bebas (independent variable). </li></ul><ul><li>Jenis-jenis Persamaan Regresi : </li></ul><ul><li>Regresi Linier : Regresi Linier Sederhana & Regresi Linier Berganda </li></ul><ul><li>Regresi Nonlinier </li></ul><ul><li>Regresi Eksponensial </li></ul><ul><li>- Bentuk Umum Regresi Linier Sederhana </li></ul><ul><li>Y = a + bX </li></ul><ul><li>Y : peubah takbebas </li></ul><ul><li>X : peubah bebas </li></ul><ul><li>a : konstanta </li></ul><ul><li>b : kemiringan </li></ul>
  3. 5. Data hasil pengamatan Regresi ∑ y= 306 ∑ x2= 555 ∑ x1= 183     68 125 38 T 6 60 100 33 S 5 40 90 29 R 4 55 85 28 Q 3 47 85 28 P 2 36 70 27 O 1 Berat Badan Harga Celana (puluh ribuan) Ukuran Celana NAMA NO.
  4. 6. Regression Descriptive Statistics 6 18.64135 92.5000 Harga Celana 6 4.23084 30.5000 Ukuran Celana 6 12.23111 51.0000 Berat Badan N Std. Deviation Mean
  5. 7. Variables Entered/Removed Model Summary Enter . Harga Celana, Ukuran Celana 1 Method Variables Removed Variables Entered Model 3.248 Durbin-Watson .127 3 2 4.445 .748 7.93132 .580 .748 .865 1 Sig. F Change df2 df1 F Change R Square Change Change Statistics Std. Error of the Estimate Adjusted R Square R Square R Model
  6. 9. Residuals Statistics 6 .254 .333 .690 .168 Centered Leverage Value 6 .662 .460 1.784 .001 Cook's Distance 6 1.270 1.667 3.451 .842 Mahal. Distance 6 1.289 -.163 1.694 -2.059 Stud. Deleted Residual 6 12.53070 -3.5050 12.9319 -19.8228 Deleted Residual 6 1.028 -.118 1.329 -1.428 Stud. Residual 6 .775 .000 1.084 -1.159 Std. Residual 6 6.14357 .0000 8.5978 -9.1957 Residual 6 11.64868 54.5050 75.7143 42.0681 Adjusted Predicted Value 6 1.35073 5.47106 7.34186 4.59157 Standard Error of Predicted Value 6 1.000 .000 1.755 -1.150 Std. Predicted Value 6 10.57622 51.0000 69.5652 38.8370 Predicted Value N Std. Deviation Mean Maximum Minimum
  7. 10. Charts
  8. 12. ∑ Y²= 16354 ∑ (X2)²= 53075 ∑ (x1)²= 5671 ∑ x2= 29290 ∑ x1y= 9552 ∑ y= 306 ∑ x2= 555 ∑ x1= 183     4624 15625 1444 8500 2584 68 125 38 T 6 3600 10000 1089 6000 1980 60 100 33 S 5 1600 8100 841 3600 1160 40 90 29 R 4 3025 7225 784 4675 1540 55 85 28 Q 3 2209 7225 784 3995 1316 47 85 28 P 2 1296 4900 729 2520 972 36 70 27 O 1 Y² (X2)² (x1)² x2y x1y Y x2 x1 NAMA NO.
  9. 13. b= (6 X 9552) - (183)(306) (6 X 5671) - (183)² = 1314 537 = 2,44 a= (306:6) – (2,44 X (183 : 6)) = 51 – (- 23,42) = 51+ 23,42 = 74,42 Y= 74,42 + 2,44x
  10. 14. b= (6 X 29290) - (555)(306) (6 X 53075) - (555) = 5910 10425 = 0, 566 a= (306:6) – (0,566 X (555 : 6)) = 51 – (52,355) = -1,355 Y= 0,566 – 1,355x

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