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The decline of water supplies in certain areas of the United States has created

ID: 3257168 • Letter: T

Question

The decline of water supplies in certain areas of the United States has created the need for increased understanding of relationships between economic factors such as crop yield and hydrologic and soil factors. An article gives data on grain sorghum yield (y, in g/m-row) and distance upslope (x, in m) on a sloping watershed. Selected observations are given in the accompanying table.

- Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.)

- Estimate true average yield when distance upslope is 75 by giving a 95% confidence interval. (Round your answers to one decimal place.)

x     0 10 20 30 45 50 70 80 100 120 140 160 170 190 y     500 585 410 465 450 475 510 445 360 405 300 415 280 345

Explanation / Answer

Answer:

The decline of water supplies in certain areas of the United States has created the need for increased understanding of relationships between economic factors such as crop yield and hydrologic and soil factors. An article gives data on grain sorghum yield (y, in g/m-row) and distance upslope (x, in m) on a sloping watershed. Selected observations are given in the accompanying table.

x    

0

10

20

30

45

50

70

80

100

120

140

160

170

190

y    

500

585

410

465

450

475

510

445

360

405

300

415

280

345

- Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.)

test statistic F=18.96 and the P-value =0.0009

- Estimate true average yield when distance upslope is 75 by giving a 95% confidence interval. (Round your answers to one decimal place.)

Estimated true average=434.7

95% CI=(402.6, 466.8)

Regression Analysis

0.612

n

14

r

-0.783

k

1

Std. Error

54.388

Dep. Var.

y    

ANOVA table

Source

SS

df

MS

F

p-value

Regression

56,076.7512

1  

56,076.7512

18.96

.0009

Residual

35,496.4631

12  

2,958.0386

Total

91,573.2143

13  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=12)

p-value

95% lower

95% upper

Intercept

512.9468

24.9522

20.557

1.01E-10

458.5808

567.3129

x    

-1.0433

0.2396

-4.354

.0009

-1.5653

-0.5212

Predicted values for: y    

95% Confidence Interval

95% Prediction Interval

x    

Predicted

lower

upper

lower

upper

Leverage

75

434.703

402.634

466.771

311.939

557.466

0.073

x    

0

10

20

30

45

50

70

80

100

120

140

160

170

190

y    

500

585

410

465

450

475

510

445

360

405

300

415

280

345

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