1 project i fall 2009. 2 3 4 5 bladder kidney leukemia lung

11

Project IProject I

Fall 2009Fall 2009

55

2

3

4

5

6

7

BLA

DD

ER

1

2

3

4

5

KID

NE

Y

4

5

6

7

8

9

LEU

KE

MIA

10

15

20

25

30

2 3 4 5 6 7

BLADDER

LUN

G

1 2 3 4 5

KIDNEY

4 5 6 7 8 9

LEUKEMIA

10 15 20 25 30

LUNG

Bladder

Kidney

Leukemia

Lung

77

Question 1: Excel, Tools, data Question 1: Excel, Tools, data Analysis, Correlation Analysis, Correlation

R2 = r2 for bivariate case

F1, n-2 =[R2/1] ÷ [1-R2 ]/ (n-2) = 0.0784*42/0.9276

F1, 42 = 3.57, critical value @ 5% F1, 40 =4.08

88

EviewsEviews

Gen eff =@rfdist(1,42)Gen density=@dfdist(eff, 1, 42)

99

Lung & Kidney CorrelationLung & Kidney Correlation

0

10

20

30

40

50

0 5 10 15

EFF

DE

NS

ITY

4.08 critical3.57

Accept H0

1111

Question 1: Excel, Tools, data Question 1: Excel, Tools, data Analysis, Correlation Analysis, Correlation

R2 = r2 for bivariate case

F1, n-2 =[R2/1] ÷ [1-R2 ]/ (n-2) = 0.0784*42/0.9276

F1, 42 = 3.57, critical value @ 5% F1, 40 =4.08

1717

a.

b.

Regression is significantEventhough R2 = 0.50,Other unspecified factorsAr work

Cigarettes smoked per Capita is significant, Prob.7/10,000 happen by chance

Coefficent 0.00445, if cigarettes smoked goes up by one per capita, death rate per 100,000 goes up by 0.004453

1818

If cigarettes smoked per capita goes up by about 1%, i.e. by25, then death rates for lung cancer go up by 25*0.0044 =0.11125 per 100, 000 or deaths per year increase by 11,125Or 0.11125/ 19.653, or about 0.6%. Called calculating elasticities at means

1919

Or run a log log regression to estimate elasticity of 0.7

2020

4. c4. c

0

2

4

6

8

10

-8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8

Series: ResidualsSample 1 44Observations 44

Mean -2.36E-15Median 0.303458Maximum 7.963441Minimum -7.226050Std. Dev. 2.997614Skewness -0.105521Kurtosis 3.471883

Jarque-Bera 0.489888Probability 0.782748

2323

Copy fitted

2424

Paste into a open group windowAfter selecting edit

2525

-10

-5

0

5

10

10 15 20 25 30

FITTED

RE

SID

2.8*10-12

4. d4. d

2929

White Test for HeteroskedasticityWhite Test for Heteroskedasticity

3030

In ExcelIn Excel

3636

4e.

3838

Q 4e: Do DC and Nevada Bias Q 4e: Do DC and Nevada Bias Results?Results?

Lung Cancer Death Rates Per 100,000 People By State, 1960

Utah

LaDC

Nev

y = 0.0053x + 6.4717

R2 = 0.4864

0

5

10

15

20

25

30

35

0 500 1000 1500 2000 2500 3000 3500 4000 4500

Cigarettes Smoked Per Capita

De

ath

Ra

tes

4141

a

b

4242

5.C Are Residuals Normal?5.C Are Residuals Normal?

0

2

4

6

8

10

12

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5


Mean 1.49E-15Median 0.057038Maximum 1.308862Minimum -1.627497Std. Dev. 0.666564Skewness -0.026203Kurtosis 2.795929


4343

5.d5.d

-2

-1

0

1

2

2 3 4 5 6 7

FITTEDBLADR

RE

SID

4444

Bladder Cancer and CigarettesBladder Cancer and CigarettesBladder Cancer Death Rates Per 100,000 Vs. Cigarettes Smoked Per Capita, 1960

Aka

Wisc

NJ

Nev

Mont

0

1

2

3

4

5

6

7

0 500 1000 1500 2000 2500 3000 3500 4000 4500

Cigarettes Smoked Per Capita

Bla

dd

er

Ca

nc

er

De

ath

Ra

te

4545

66cigarettes smoked per capita Vs, Income Per Capita By State 1960

AZ

Utah

DCNev

y = 0.9057x + 532.66

R2 = 0.5261

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 500 1000 1500 2000 2500 3000 3500

Income Per Capita $

Cig

are

tte

s P

er

Ca

pit

a

4646

77

a

b

4747

7. C Are the Residuals Normal?7. C Are the Residuals Normal?

0

2

4

6

8

10

-8 -6 -4 -2 0 2 4 6 8


Mean -2.88E-15Median 0.166719Maximum 8.014785Minimum -7.153882Std. Dev. 2.888455Skewness 0.017645Kurtosis 3.731293


4848

Economic and Health SignificanceEconomic and Health Significance• Smoking is hazardous to your health, especially

for lung, bladder and Kidney cancer• Intensity of smoking, e.g cigarettes smoked per

dollar of income and income per capita affect lung cancer death rates– Smoking intensity may be reduced by advertising

health hazards and by imposing an excise tax– Development, as measured by income per capita may

create dangerous toxins that cause lung cancer, e.g. acid rain from coal smoke stacks, particlates in the air, smog etc.

4949

Beyond The ProjectBeyond The Project

5050

Lung = a{[(cigs/pop)/(Inc/pop)][Inc/pop]}b exp(e)lnLung = lna + b* cigs/$ + b*(Inc/pop) + elnLung = lna + b*(cigs/pop) – b*(inc/pop) + b(inc/pop) + elnLung = lna + b*(cigs/pop) + e

5252

Bladder Cancer Rate

Lung Cancer Rate

Kidney cancer Rate

Cigarettes/pop Income/pope

eK

eL

eB

Conjecture for 1960

1 project i fall 2009. 2 3 4 5 bladder kidney leukemia lung

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