Based on the charts below, Determine whether a
statistically reliable oil consumption model can be estimated
Variables...
Based on the charts below, Determine whether a
statistically reliable oil consumption model can be estimated
Variables
Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
Number People, Home
Index, Degree Days, Customerb
.
Enter
a. Dependent Variable:
Oil Usage
b. All requested
variables entered.
Model
Summary
Model
R
R Square
Adjusted R Square
Std. Error of the
Estimate
1
.889a
.790
.766
85.445
a. Predictors:
(Constant), Number People, Home Index, Degree Days, Customer
ANOVAa
Model
Sum of Squares
df
Mean Square...
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
109,780
3
36,593
617,763...
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
109,780
3
36,593
617,763
,030a
Residual
10,722
181
,059
Total
120,501
184
a. Predictors:
(Constant), F4, F2, F3
b. Dependent Variable:
F1
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
,356
,105
3,373
,001
F2
-,269
,026
-,699
-2,997
,030
F3
,030
,028
,570
2,103
,021
F4
,859
,024
,989
1,112
,141
a. Dependent Variable:
F1
a- Write down the hypothesis, p-...
1. The following output is from a multiple regression analysis
that was run on the variables...
1. The following output is from a multiple regression analysis
that was run on the variables FEARDTH (fear of
death) IMPORTRE (importance of religion),
AVOIDDTH (avoidance of death),
LAS (meaning in life), and
MATRLSM (materialistic attitudes). In the
regression analysis, FEARDTH is the criterion
variable (Y) and IMPORTRE,
AVOIDDTH, LAS, and
MATRLSM are the predictors (Xs). The SPSS output
is provided below, followed by a number of questions (12 points
total).
Descriptive
Statistics
Mean
Std. Deviation
N
feardth
27.0798
8.08365...
Regression: First, choose any metric variable as the dependent
variable and then choose any three other...
Regression: First, choose any metric variable as the dependent
variable and then choose any three other metric variables as
independent variables. HOWEVER, this process must be repeated until
you find a model that produces a significant F-calc (p-value (sig)
<.05). Thus, you may have to sort through several combinations
of dependent and independent variables before finding a combination
that produces a significant F-calc. This is actually quite easy to
do in SPSS using the drop down menus as shown in...
10. In Exercise 6, we examined the relationship between years of
education and hours of television...
10. In Exercise 6, we examined the relationship between years of
education and hours of television watched per day. We saw that as
education increases, hours of television viewing decreases. The
number of children a family has could also affect how much
television is viewed per day. Having children may lead to more
shared and supervised viewing and thus increases the number of
viewing hours. The following SPSS output displays the relationship
between television viewing (measured in hours per day)...