Estriol Level and Birth Weight.The data from Exercise 14.42 for estriol levels of pregnant women and birth weights of their children are on the WeissStats site. Do the data provide sufficient evidence to conclude that estriol level and birth weight are positively linearly correlated?

Short Answer

Expert verified

Thus, the data provide sufficient evidence to conclude that estriol level and birth weight are positively linearly correlated at 5%significance level.

Step by step solution

01

Step 1:Given information

The data from Exercise 14.42 for estriol levels of pregnant women and birth weights of their children are on the WeissStats site

02

Step 2:Explaination

Check whether or not it is reasonably apply the correlation t-test procedure by using the data from Exercise14.42

- From the residual plot versus estriol level, there is an increasing level of variability.

- From the normal probability plot of residuals, it is clear that the residuals are roughly linear pattern.

Hence, the assumption 2 for the regression inferences is violated for the variables weight and Estriol level. But the normality assumption for the regression inferences is not violated.

Therefore, it is reasonably applying the correlation t-test procedure for given data.

Check whether the data provide sufficient evidence to conclude that estriol level and birth weight are positively linearly correlated or not.

The test hypotheses are as follows:

Null hypothesis:

H0:ρ=0

That is, the estriol level and birth weight are not positively linearly correlated.

Alternative hypothesis:

Ha:ρ>0

That is, the estriol level and birth weight are positively linearly correlated.

Obtain the correlation and p-value between estriol level and birth weight by using MINITAB.

MINITAB procedure:

Step 1: Select Stat >Basic Statistics > Correlation.

Step 2: In Variables, select estriol level and birth weight from the box on the left.

Step 3: ClickOK.

MINITAB output:

03

Step 3:Conclusion

Use the significance level, α=0.05.

Here, p-value is lesser than the level of significance.

That is, p-value (=0)<α(=0.05).

Therefore, by the rejection rule, it can be concluded that there is evidence to reject the null hypothesis H0at α=0.05.

Thus, the data provide sufficient evidence to conclude that estriol level and birth weight are positively linearly correlated at 5%significance level.

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Most popular questions from this chapter

Gas Guzzlers. The data from Exercise 14.41 for gas mileage and engine displacement of 121 vehicles are on the WeissStats site. Specified value of the predictor variable: 3.0L.

a. Decide whether you can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b)-(f).

b. Determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.

c. Find and interpret a 95%confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.

d. Determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.

e. Find and interpret a 95%prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.

f. Compare and discuss the differences between the confidence interval that you obtained in part (c) and the prediction interval that you obtained in part (e).

To find and interpret a confidence interval, at the specified confidence level 99%for the slope of the population regression line that relates the response variables to the predictor variable.

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a. compute the standard error of the estimate and interpret your answer

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In this Exercise 14.49, we repeat the information from Exercises 14.13.

a. Decide, at the 10%significance level, whether the data provide sufficient evidence to conclude that xis useful for predicting y:

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x312y-40-5 y^=1-2x

In each of Exercises 14.64-14.69, apply Procedure 14.2 an page 567 to find and interpret a confidence interval, at the specified confidence level for the slope of the population regression line that relates rite response variable to the predicter variable.

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