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The following are the pulmonary blood flow (PBF) and pulmonary blood volume (PBV

ID: 3204075 • Letter: T

Question

The following are the pulmonary blood flow (PBF) and pulmonary blood volume (PBV) values recorded for 16 infants and children with congenital heart disease:

y

PBV (ml/sqM)

167
280
394
420
303
429
602
522
224
291

233

370

531

516

211

439

X

PBF (L/min/sqM)

4.32
3.40

6.25

17.30

12.30
13.99

8.74
8.90
5.87
5.00

3.51

4.24

19.41

16.61

7.21

11.60

Find the regression equation describing the linear relationship between the two variables. Let = .05. Use SPSS to answer the question

y

PBV (ml/sqM)

167
280
394
420
303
429
602
522
224
291

233

370

531

516

211

439

X

PBF (L/min/sqM)

4.32
3.40

6.25

17.30

12.30
13.99

8.74
8.90
5.87
5.00

3.51

4.24

19.41

16.61

7.21

11.60

Explanation / Answer

Please note that we cannot use paid softwares such as spss,sas to answer such question on this forum. However , we shall provide you a solution using the open source alternative R , the concepts and workings remain the same. The complete R snippet is as follows

y<-c(167,280,394,420,303,429,602,522,224,291,233,370,5310,516,211,439)
x<-c(4.32,3.4,6.25,17.3,12.3,13.99,8.74,8.9,5.87,5,3.52,4.24,19.41,16.61,7.21,11.6)


# fit the model linear regression

fit <- lm(y ~ x)

# analyse the results

summary(fit)

The results are

> summary(fit)

Call:
lm(formula = y ~ x)

Residuals:
Min 1Q Median 3Q Max
-1299.5 -590.1 4.0 218.2 3313.9

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -548.75 554.04 -0.99 0.339
x 131.11 52.23 2.51 0.025 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1069 on 14 degrees of freedom
Multiple R-squared: 0.3104,   Adjusted R-squared: 0.2611
F-statistic: 6.301 on 1 and 14 DF, p-value: 0.02497

as the p value(0.024) is less than 0.05 , we can conclude that the relationship between the variables is significant and the equation can be formed using the coefficient table as

Y = -548.7+ 131.11X

The results from the spss would also be the same , only the tool is different.

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