RQ 1:
Model Summaryb
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.618a
.382
.351
6.39851
a. Predictors: (Constant), quiz5, quiz4, quiz2, quiz3, quiz1
b. Dependent Variable: final
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
2509.039
5
501.808
12.257
.000a
Residual
4053.151
99
40.941
Total
6562.190
104
a. Predictors: (Constant), quiz5, quiz4, quiz2, quiz3, quiz1
b. Dependent Variable: final
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
38.700
3.360
11.518
.000
quiz1
.286
.566
.089
.505
.615
quiz2
.942
.661
.193
1.425
.157
quiz3
.922
.572
.268
1.611
.110
quiz4
.033
.518
.010
.065
.949
quiz5
.699
.500
.155
1.399
.165
a. Dependent Variable: final
Coefficient of determination R2 value of 38% denotes that 38% of the variation in the final score can be explained by the quiz scores.
quiz5
+
quiz5
+
quiz5
+
quiz5
+
quiz5
+
quiz5
+
quiz5
+*++++++++++
0.286 is the slope of quiz 1; similarly 0.942 is of quiz 2, 0.922 is of quiz 3 and 0.033 of quiz 4 and 0.699 of quiz 5.
The slope informs the changes in y in relation to x and therefore, as quizzes score increases, we can expect increase in the final score percentage. When the quiz 2 response increases by 1 percentage, we expect the final score to increase 0.942 percent which is the highest among all quizzes.
quiz5
++
quiz5
++
quiz5
++
quiz5
++
quiz5
++
quiz5
++*++++++
RQ 2:
This graph can be interpreted as positive relation between previous year GPA and total score in statistics class (Aron, Aron and Coups, 2008). With the increase in the previous year gpa, the total score is also increasing.
quiz5
+++
quiz5
+++
quiz5
+++
quiz5
+++*++++
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.432a
.187
.179
13.86296
a. Predictors: (Constant), prevgpa
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
4549.013
1
4549.013
23.670
.000a
Residual
19794.702
103
192.182
Total
24343.714
104
a. Predictors: (Constant), prevgpa
b. Dependent Variable: total
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
76.510
5.127
14.922
.000
quiz5
++
8.659
1.780
.432
4.865
.000
a. Dependent Variable: total
quiz5
+++++++++++++
quiz5
+++++++++++++
quiz5
+++++++++++++*+++++++++++
RQ 3: Final exam points are the dependent variable and short term IQ score and previous year gpa are dependent variable.
Regression equation, Final = B0 + B1IQ + B2 prevgpa
Running multiple linear regression, we get
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.507a
.257
.243
6.91219
a. Predictors: (Constant), prevgpa, iq
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1688.794
2
844.397
17.673
.000a
Residual
4873.396
102
47.778
Total
6562.190
104
a. Predictors: (Constant), prevgpa, iq
b. Dependent Variable: final
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
38.231
8.241
4.639
.000
iq
.093
.083
.117
1.130
.261
quiz5
++
4.485
1.080
.431
4.153
.000
a. Dependent Variable: final
quiz5
+++++++++++++++++++++++
quiz5
+++++++++
Final = 38.23 + .093IO + 4.485 prevgpa
= 38.23 + 0.093 x 120 + 4.485 x 3.35
= 64.4147
quiz5
+++++
Arthur Aron, Elaine N. Aron, Elliot Coups. (2008). Statistics for psychology (5th ed.). Prentice Hall.
