(Soalan 2] Based on the given multiple regression output tables below, answer the following questions: (Berdasarkan kepada jadual dapatan regresi berganda yang dinyatakan di bawah, jawab soalan-soalan yang berikut:) Model Summary Adjusted R Square Std. Error of the Estimate Durbin- Watson Model R R Square .842 710 .630 109.430 1.158 ANOVA Sum of Squares Model df Mean Square Sig. Regression 321946.82 3. 107315.6 8.96 0.0027 Residual 131723.20 11 11974.8 Total 453670.00 14 Coefficients Standardized Coefficients Unstandardized Coefficients Model Std. Error Beta Sig. 167.46 (Constant) X Variable I X Variable 2 657.053 3.92 .0024 5.7103 1.792 101 3.19 0087 -0.4169 0.322 -077 -1.29 2222 X Variable 3 -3.4715 1.443 -7.996 -2.41 0349
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
a) explain on he strenght and variation of the model (multiple regression)
b) At a-value =0.01. test whether there is a significiant relationship between the dependent variable (y) and the independant variables x1, x2 and x3
![Question 2
[Soalan 2]
Based on the given multiple regression output tables below, answer the following
questions:
Berdasarkan kepada jadual dapatan regresi berganda yang dinyatakan di bawah, jawab soalan-soalan
yang berikut:]
Model Summary
Adjusted R
Square
Std. Error of the
Durbin-
Model
R
R Square
Estimate
Watson
842-
710
630
109.430
1.158
ANOVA
Sum of
Mean Square
Sig.
Model
Squares
df
F
Regression
321946.82
3
107315.6
8.96
0.0027
Residual
131723.20
11
11974.8
Total
453670.00
14
Coefficients
Standardized
Unstandardized Coefficients
Coefficients
Model
B
Std. Error
Beta
Sig.
(Constant)
X Variable 1
X Variable 2
657.053
167.46
3.92
.0024
5.7103
1.792
-101
3.19
0087
-0.4169
0.322
077
-1.29
2222
X Variable 3
-3.4715
1.443
-7.996
-2.41
0349](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1f344525-ee88-4f63-83c1-857027649b79%2F283be5a1-0ac6-4091-9982-dab7d2e3ecd1%2Fvcyg2cd_processed.jpeg&w=3840&q=75)
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
