For each exercise, decide at 10% significance level, whether the data provide sufficient evidence to reject the null hypothesis in favour of alternate hypothesis

Ha :pnot=0.

x04312
y19843

Short Answer

Expert verified

We don't reject Ha : pnot=0, and state that the variables are linearly correlated.

Step by step solution

01

Correlation Coefficient 

Sample correlation coefficient is calculated by : r=zxzy/(n-1)

where zxn=(xn-mean)/standarddeviation, and same for zyn

Using excel and above formula concept,r=0.9325

02

Hypothesis Testing 

rnot=0for sample needs to be tested using hypothesis testing, to ensure that the population correlation parameterp (rho) is non zero.

t=r/(1-r2)/(n-2)0.9325/(1-0.9325)/(5-2)0.9325/0.0675/30.9325/0.02250.9325/0.15t=6.216

As t calculated value is greater than t value for 10%significance level ie 0.05each side, and p value =0.02is also lesser than p at the same significance level

So, we reject the null hypothesis H0 : p=0in favour of alternate hypothesis H1 : pnot=0. Hence, the variables are linearly correlated.

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Most popular questions from this chapter

Gas Guzzlers. Use the data on the WeissStats site for gas mileage and engine displacement for 121 vehicles referred to in Exercise 14.41.

In Exercises 14.98-14.108, use the technology of your choice to do the following tasks.
a. Decide whether your can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b) - (h).
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).

14.103 High and Low Temperature. The data from Exercise 14.31for average high and low temperatures in January of a random sample, of 50cities are on the WeissStats site. Specified value of the predictor variable: 55°F.

14.97 Study Time and Score. Following are the data on total hours studied over 2 weeks and test score at the end of the 2 weeks from Exercise 14.27.

x
10
15
12
20
8
16
14
22
y
91
81
84
74
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84
80


a. Determine a point estimate for the mean test score of all beginning calculus students who study for 15hours.
b. Find a 99% confidence interval for the mean test score of all beginning calculus students who study for 15 hours.
c. Find the predicted test score of a beginning calculus student who studies for 15 hours.
d. Determine a 99% prediction interval for the test score of a beginning calculus student who studies for 15hours.

The data from Exercise 14.43 for volume, in cubic feet, and diameter at breast height, in inches, for 70 shortleaf pines are on the WeissStats site.

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).

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