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Concerns about global warming have led to studies of the relationship between gl

ID: 3227020 • Letter: C

Question

Concerns about global warming have led to studies of the relationship between global temperature and the concentration of CO2. Listed below are the concentrations of CO2 in ppm (parts per million) and temperatures in Celsius [based on data from the Earth Policy Institute]. Is there a linear relationship between temperature and the concentration of CO2 at = 0.05? [fyi: safe is listed as 350 ppm]

CO2 314 317 320 326 331 339 346 354 361 369

Temperature 13.9 14 13.9 14.1 14.0 14.3 14.1 14.5 14.5 14.4

a) r = ________

b) Critical value(s) = ___________

c) If there is a linear correlation, state the equation of the line: _________________________ [please don’t write y = mx + b. I want the equation for this study]

d) If there is a linear correlation, determine the predicted CO2 levels if the temperature rises to 14.8 degrees Celsius. ___________

Explanation / Answer

Answer:

Concerns about global warming have led to studies of the relationship between global temperature and the concentration of CO2. Listed below are the concentrations of CO2 in ppm (parts per million) and temperatures in Celsius [based on data from the Earth Policy Institute]. Is there a linear relationship between temperature and the concentration of CO2 at = 0.05? [fyi: safe is listed as 350 ppm]

CO2 314 317 320 326 331 339 346 354 361 369

Temperature 13.9 14 13.9 14.1 14.0 14.3 14.1 14.5 14.5 14.4

a) r = 0.8920

Correlation Matrix

co2

temp

co2

1.000

temp

0.8920

1.000

10

sample size

± .632

critical value .05 (two-tail)

± .765

critical value .01 (two-tail)

b) Critical value(s) r = (-0.632, 0.632)

since calculated r=0.892 > 0.632, correlation is significant.

c) If there is a linear correlation, state the equation of the line:

CO2 = 72.8743*Temp -694.9281

[please don’t write y = mx + b. I want the equation for this study]

Regression Analysis

0.796

n

10

r

0.892

k

1

Std. Error

9.243

Dep. Var.

co2

ANOVA table

Source

SS

df

MS

F

p-value

Regression

2,660.6389

1  

2,660.6389

31.14

.0005

Residual

683.4611

8  

85.4326

Total

3,344.1000

9  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=8)

p-value

95% lower

95% upper

Intercept

-694.9281

185.0619

-3.755

.0056

-1,121.6817

-268.1746

temp

72.8743

13.0585

5.581

.0005

42.7613

102.9872

d) If there is a linear correlation, determine the predicted CO2 levels if the temperature rises to 14.8 degrees Celsius. ___________

when co2=14.8,

predicted CO2 = 72.8743*14.8 -694.9281

=383.61

Correlation Matrix

co2

temp

co2

1.000

temp

0.8920

1.000

10

sample size

± .632

critical value .05 (two-tail)

± .765

critical value .01 (two-tail)

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