Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 2.205 8.663 .255 .802 -15.996 20.406 weight (kg) 1.201 .093 .950 12.917 .000 1.006 1.396 a. Dependent Variable: arterial blood pressure Find the simple linear regression equation between blood pressure (y) and body weight (x2). Is this a significant regression? Ho: B=0 Ha: B does not = 0 Test statistic and value: t=12.91 p-value: Statistical conclusion: Written conclusion: If someone has a weight of 93.5 kg, what would you predict their blood pressure to be based on the results of this sample Now, include all of the variables in a multiple regression equation to predict blood pressure. What is the final model?? (hint - run the final analysis with only those variables that are statistically significant) Find the simple linear regression equation between blood pressure (y) and body weight (x2). Is this a significant regression? Ho: B=0 Ha: B does not = 0 Test statistic and value: t=12.91 p- value: Statistical conclusion: Written conclusion: If someone has a weight of 93.5 kg, what would you predict their blood pressure to be based on the results of this sample Now, include all of the variables in a multiple regression equation to predict blood pressure. What is the final model? ? (hint - run the final analysis with only those variables that are statistically significant) Solution Regression line is y= 2.205 +1.201*weight p-value: = 2*P(t>12.91) =0 (from student t table) Statistical conclusion: Since the p-value is 0, we reject Ho. Written conclusion: So we can conclude that it is a significant regression predict their blood pressure: 2.205 +1.201*93.5 =114.4985 weightis on the final model.

1. Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
95.0% Confidence Interval for B
B
Std. Error
Beta
Lower Bound
Upper Bound
1
(Constant)
2.205
8.663
.255
.802
-15.996
20.406
weight (kg)
1.201
.093
.950

2. 12.917
.000
1.006
1.396
a. Dependent Variable: arterial blood pressure
Find the simple linear regression equation between blood pressure (y) and body weight (x2).

3. Is this a significant regression?
Ho: B=0

4. Ha: B does not = 0
Test statistic and value: t=12.91
p-value:

5. Statistical conclusion:
Written conclusion:
If someone has a weight of 93.5 kg, what would you predict their blood pressure to be based on
the results of this sample

6. Now, include all of the variables in a multiple regression equation to predict blood pressure.
What is the final model?? (hint - run the final analysis with only those variables that are
statistically significant)

7. Find the simple linear regression equation between blood pressure (y) and body weight (x2). Is
this a significant regression? Ho: B=0 Ha: B does not = 0 Test statistic and value: t=12.91 p-
value: Statistical conclusion: Written conclusion: If someone has a weight of 93.5 kg, what
would you predict their blood pressure to be based on the results of this sample Now, include all
of the variables in a multiple regression equation to predict blood pressure. What is the final
model? ? (hint - run the final analysis with only those variables that are statistically significant)
Solution
Regression line is y= 2.205 +1.201*weight
p-value: = 2*P(t>12.91) =0 (from student t table)
Statistical conclusion:
Since the p-value is 0, we reject Ho.
Written conclusion:
So we can conclude that it is a significant regression
predict their blood pressure:
2.205 +1.201*93.5 =114.4985

8. weightis on the final model