Frencia Kam Wijaya / 2201732531 Jacklyn Elza Ivane / 2201740804 Silvia Firmansyah / 2201733950

1. Regression Analysis
Frencia Kam Wijaya /2201732531
Jacklyn Elza Ivane /2201740804
Silvia Firmansyah /2201733950

2. What is Regression Analysis?
Regression analysis is used to study the relationship between two or more
variables. Moreover, the regression technique is used to observe changes in
the dependent variable with changes in the independent variables. The
parameters in the regression equation are obtained by using least square
method.
• Independent variable represents the inputs make the changes in the
dependent variable.
• Dependent variable represents the output based on the values of the
independent variable.

3. Regression Analysis
There are two types of regression techniques:
• Linear Regression.
• Non-Linear Regression.
Linear regression analysis is categorized into two types:
• Simple Linear Regression.
• Multiple Linear Regression.

4. Simple Linear Regression
Simple linear regression is used to study the linear relationship between one
independent and one dependent variable.
The regression equation is
𝑦 = 𝑏0 + 𝑏1 𝑥
𝑏0 = 𝑡ℎ𝑒 𝑖𝑛𝑡𝑒𝑟𝑐𝑒𝑝𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑙𝑖𝑛𝑒
𝑏1 = 𝑡ℎ𝑒 𝑠𝑙𝑜𝑝𝑒 𝑜𝑓 𝑡ℎ𝑒 𝑙𝑖𝑛𝑒 or regression coefficient
𝑦 = 𝑡ℎ𝑒 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑣𝑎𝑙𝑢𝑒
𝑥 = 𝑖𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝑣𝑎𝑙𝑢𝑒

5. Multiple Linear Regression
Multiple linear regression is used to study the linear relationship between one
dependent variable and more than two independent variables.
The regression equation is
𝑦 = 𝑏0 + 𝑏1 𝑥1 + 𝑏2 𝑥2 + ⋯ + 𝑏 𝑛 𝑥 𝑛
𝑏0 = 𝑡ℎ𝑒 𝑖𝑛𝑡𝑒𝑟𝑐𝑒𝑝𝑡 𝑜𝑓 𝑡ℎ𝑒 𝑙𝑖𝑛𝑒
𝑏1, 𝑏2, … , 𝑏 𝑛 = 𝑡ℎ𝑒 𝑠𝑙𝑜𝑝𝑒 𝑜𝑓 𝑡ℎ𝑒 𝑙𝑖𝑛𝑒 or regression coefficient
𝑦 = 𝑡ℎ𝑒 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑣𝑎𝑙𝑢𝑒
𝑥1, 𝑥2, … , 𝑥 𝑛 = 𝑖𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝑣𝑎𝑙𝑢𝑒

6. D
A
T
A
x y x - y -
2 10 -0.7 -2 1.4 0.49
3 12 0.3 -9 -2.7 0.09
2 11 -0.7 -10 7 0.49
4 13 1.3 -8 -10.4 1.69
5 14 2.3 -7 -16.1 5.29
3 11 0.3 -9 -2.7 0.09
1 10 -1.7 -11 18.7 2.89
4 13 1.3 -8 -10.4 1.69
2 14 -0.7 -10 7 0.49
1 12 -1.7 -11 18.7 2.89
Total 27 120 10.5 16.1
Rata-rata 2.7 12 1.05 1.61
𝑥 𝑦 𝑥 − 𝑥 𝑦 − 𝑦 𝑥 − 𝑥 2
Contoh Soal Simple Linear Regression

7. b1 =
𝑥𝑖 − 𝑥 𝑦𝑖 − 𝑦
𝑥𝑖 − 𝑥 2
= 10.5 = 0.65
16.1
b0 =
=12 - 0.65(2.7)
=10.245
𝑦 − 𝑏1 𝑥
10.25 + 0.65x𝑦 =
Slope for the Estimated Regreesion
Equation
y-Intercept for the Estimated Regression Equation
Estimated Regression Equation

8. Daftar Pustaka
https://www.chegg.com/homework-help/definitions/regression-analysis-31
https://newcontent.binus.ac.id/data_content/general_course_outline/course_outl
ine/main_material/RS1/007398/2018082012523400004433_Z0227003012015406
1Materi%2010%20-%20Z0227%20(Simple%20Linear%20Regression).pptx