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Pengujian Parameter Regresi Ganda Pertemuan 22 Matakuliah: L0104/Statistika Psikologi Tahun: 2008.

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Presentation on theme: "Pengujian Parameter Regresi Ganda Pertemuan 22 Matakuliah: L0104/Statistika Psikologi Tahun: 2008."— Presentation transcript:

1 Pengujian Parameter Regresi Ganda Pertemuan 22 Matakuliah: L0104/Statistika Psikologi Tahun: 2008

2 Bina Nusantara University 2 Learning Outcomes Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu : Mahasiswa akan dapat menghasilkan simpulan hasil uji intersep dan koefisien regresi.

3 Bina Nusantara University 3 Outline Materi Pengujian intersep Pengujian koefisien regresi Analisis varians regresi ganda

4 Bina Nusantara University 4 Using the Estimated Regression Equation for Estimation and Prediction The procedures for estimating the mean value of y and predicting an individual value of y in multiple regression are similar to those in simple regression. We substitute the given values of x 1, x 2,..., x p into the estimated regression equation and use the corresponding value of y as the point estimate. The formulas required to develop interval estimates for the mean value of y and for an individual value of y are beyond the scope of the text. Software packages for multiple regression will often provide these interval estimates. ^

5 Bina Nusantara University 5 Contoh Soal: Programmer Salary Survey A software firm collected data for a sample of 20 computer programmers. A suggestion was made that regression analysis could be used to determine if salary was related to the years of experience and the score on the firm’s programmer aptitude test. The years of experience, score on the aptitude test, and corresponding annual salary ($1000s) for a sample of 20 programmers is shown on the next slide.

6 Bina Nusantara University 6 Contoh Soal: Programmer Salary Survey Exper. Score Salary Exper. Score Salary

7 Bina Nusantara University 7 Contoh Soal: Programmer Salary Survey Multiple Regression Model Suppose we believe that salary (y) is related to the years of experience (x 1 ) and the score on the programmer aptitude test (x 2 ) by the following regression model: y =  0 +  1 x 1 +  2 x 2 +  where y = annual salary ($000) x 1 = years of experience x 2 = score on programmer aptitude test

8 Bina Nusantara University 8 Contoh Soal: Programmer Salary Survey Multiple Regression Equation Using the assumption E (  ) = 0, we obtain E(y ) =  0 +  1 x 1 +  2 x 2 Estimated Regression Equation b 0, b 1, b 2 are the least squares estimates of  0,  1,  2 Thus y = b 0 + b 1 x 1 + b 2 x 2 ^

9 Bina Nusantara University 9 Contoh Soal: Programmer Salary Survey Solving for the Estimates of  0,  1,  2 ComputerPackage for Solving MultipleRegressionProblemsComputerPackage MultipleRegressionProblems b 0 = b 1 = b 1 = b 2 = b 2 = R 2 = etc. b 0 = b 1 = b 1 = b 2 = b 2 = R 2 = etc. Input Data Least Squares Output x 1 x 2 y x 1 x 2 y

10 Bina Nusantara University 10 Contoh Soal: Programmer Salary Survey Minitab Computer Output The regression is Salary = Exper Score Predictor Coef Stdev t- ratio p Constant Exper Score s = R-sq = 83.4% R-sq(adj) = 81.5%

11 Bina Nusantara University 11 Contoh Soal: Programmer Salary Survey Minitab Computer Output (continued) Analysis of Variance SOURCE DF SS MS F P Regression Error Total

12 Bina Nusantara University 12 Contoh Soal: Programmer Salary Survey F Test – HypothesesH 0 :  1 =  2 = 0 H a : One or both of the parameters is not equal to zero. – Rejection Rule For  =.05 and d.f. = 2, 17: F.05 = 3.59 Reject H 0 if F > – Test Statistic F = MSR/MSE = /5.85 = – Conclusion We can reject H 0.

13 Bina Nusantara University 13 COntoh Soal: Programmer Salary Survey t Test for Significance of Individual Parameters – Hypotheses H 0 :  i = 0 H a :  i = 0 – Rejection Rule For  =.05 and d.f. = 17, t.025 = 2.11 Reject H 0 if t > 2.11 – Test Statistics – Conclusions Reject H 0 :  1 = 0 Reject H 0 :  2 = 0

14 Bina Nusantara University 14 Qualitative Independent Variables In many situations we must work with qualitative independent variables such as gender (male, female), method of payment (cash, check, credit card), etc. For example, x 2 might represent gender where x 2 = 0 indicates male and x 2 = 1 indicates female. In this case, x 2 is called a dummy or indicator variable. If a qualitative variable has k levels, k - 1 dummy variables are required, with each dummy variable being coded as 0 or 1. For example, a variable with levels A, B, and C would be represented by x 1 and x 2 values of (0, 0), (1, 0), and (0,1), respectively.

15 Bina Nusantara University 15 Selamat Belajar Semoga Sukses.


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