The temperature in degrees Fahrenheit and the number of emergency calls are show
ID: 2946718 • Letter: T
Question
The temperature in degrees Fahrenheit and the number of emergency calls are shown below. Determine if there is a relationship between the temperature and the number of emergency calls received. Use .05 significance.
Number of Calls (Y)
Temperature (X)
7
68
4
74
8
82
10
88
11
93
9
99
13
101
What is the p value and is it significant?
Select one:
a. .1898, no it is not significant.
b. .0267, yes it is significant.
c. .2162, yes it is significant.
d. 9.6335, yes it is significant.
The temperature in degrees Fahrenheit and the number of emergency calls are shown below. Determine if there is a relationship between the temperature and the number of emergency calls received. Use .05 significance.
Number of Calls (Y)
Temperature (X)
7
68
4
74
8
82
10
88
11
93
9
99
13
101
If x is equal to 80, what is the value of y?
Select one:
a. Unable to determine because the relationship is not significant.
b. 7.0.
c. 7.6399.
d. 8.1088.
Number of Calls (Y)
Temperature (X)
7
68
4
74
8
82
10
88
11
93
9
99
13
101
Explanation / Answer
We use the regression model to find the relationship between the temprature and emergency calls received.
Below is the regression output of Excel.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.811369
R Square
0.658319
Adjusted R Square
0.589983
Standard Error
1.864238
Observations
7
ANOVA
df
SS
MS
F
Significance F
Regression
1
33.48022
33.48022
9.633531
0.026738
Residual
5
17.37692
3.475384
Total
6
50.85714
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
-7.5441
5.331028
-1.41513
0.216184
-21.2479
6.159745
X Variable 1
0.189766
0.06114
3.103793
0.026738
0.032601
0.346932
1. From the output of regression,
The P value = 0.0267
P value < 0.05 so we reject null hypothesis 5% level of significance.
We conclude that it is significant.
2. From the above output,
Regression equation is Y = 0.1898*X – 7.5441
If X = 80 then the value of Y = 0.1898*80 – 7.5441 = 7.6399
The value of Y = 7.6399.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.811369
R Square
0.658319
Adjusted R Square
0.589983
Standard Error
1.864238
Observations
7
ANOVA
df
SS
MS
F
Significance F
Regression
1
33.48022
33.48022
9.633531
0.026738
Residual
5
17.37692
3.475384
Total
6
50.85714
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
-7.5441
5.331028
-1.41513
0.216184
-21.2479
6.159745
X Variable 1
0.189766
0.06114
3.103793
0.026738
0.032601
0.346932
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.