tate the predictors available in this model. b. Determine the multiple regression model for this analysis. c.Interpret the slope in this mode
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. State the predictors available in this model.
b. Determine the multiple regression model for this analysis.
c.Interpret the slope in this model.
(d) Based on your answer in (b), explain on the strength and the variation of the model.
(e) At α-value=0.01, test whether there is a significant relationship between the dependent variable (Y) and the independent 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
Estimate
Durbin-
Model
R
R Square
Watson
.842-
.710
.630
109.430
1.158
ΑNOVA
Sum of
Squares
Model
df
Mean Square
F
Sig.
Regression
321946.82
3
107315.6
8.96
J0.0027
Residual
131723.20
11
11974.8
Total
453670.00
14
Coefficients
Standardized
Unstandardized Coefficients
Coefficients
Model
B
Std. Error
Beta
Sig.
(Constant)
657.053
167.46
3.92
.0024
X Variable 1
X Variable 2
X Variable 3
5.7103
1.792
-.101
3.19
.0087
-0.4169
0.322
-.077
-1.29
.2222
-3.4715
1.443
-7.996
-2.41
.0349](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff0437a13-a8e8-4817-b7ca-e7bc4db901c6%2F05eb7ac3-1ceb-4d93-bbd0-5232cec8eaca%2F77pkqdc_processed.jpeg&w=3840&q=75)
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