Q24BSC Testing for a Linear Correlation... [FREE SOLUTION]

Chapter 10: Q24BSC (page 468)

Testing for a Linear Correlation. In Exercises 13鈥�28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of A = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.)
Manatees Listed below are numbers of registered pleasure boats in Florida (tens of thousands) and the numbers of manatee fatalities from encounters with boats in Florida for each of several recent years. The values are from Data Set 10 鈥淢anatee Deaths鈥� in Appendix B. Is there sufficient evidence to conclude that there is a linear correlation between numbers of registered pleasure boats and numbers of manatee boat fatalities?
Pleasure Boats
99
99
97
95
90
90
87
90
90
Manatee Fatalities
92
73
90
97
83
88
81
73
68

Short Answer

Expert verified

The scatterplot is shown below:

The value of the correlation coefficient is 0.341.

The p-value is 0.369.

There is not enough evidence to support the claim that there existsa linear correlation betweenthe counts of pleasure boats and manatee fatalities.

Step by step solution

Given information

The data is listed for the number of registered pleasure boats and manatee fatalities in Florida.

Pleasure Boats	Manatee Fatalities
99	92
99	73
97	90
95	97
90	83
90	88
87	81
90	73
90	68

Sketch a scatterplot

A scatterplot determines the pattern in any paired set of data.

Steps to sketch a scatterplot:

Mark the two variables as pleasure boats and manatee fatalities on x and y-axis, respectively.
Mark the observations in a paired form on the graph.

The scatterplotis shown below.

Compute the measure of the correlation coefficient

The correlation coefficient formula is

\(r = \frac{{n\sum {xy} - \left( {\sum x } \right)\left( {\sum y } \right)}}{{\sqrt {n\left( {\sum {{x^2}} } \right) - {{\left( {\sum x } \right)}^2}} \sqrt {n\left( {\sum {{y^2}} } \right) - {{\left( {\sum y } \right)}^2}} }}\).

Let variable x be pleasure boats counts and y be the count of manatee fatalities.

The valuesare listedin the table below:

x	y	\({x^2}\)	\({y^2}\)	\(xy\)
99	92	9801	8464	9108
99	73	9801	5329	7227
97	90	9409	8100	8730
95	97	9025	9409	9215
90	83	8100	6889	7470
90	88	8100	7744	7920
87	81	7569	6561	7047
90	73	8100	5329	6570
90	68	8100	4624	6120
\(\sum x = 837\)	\(\sum y = 745\)	\(\sum {{x^2}} = 78005\)	\(\sum {{y^2} = } \;62449\)	\(\sum {xy\; = \;} 69407\)

Substitute the values in the formula:

\(\begin{aligned} r &= \frac{{9\left( {69407} \right) - \left( {837} \right)\left( {745} \right)}}{{\sqrt {9\left( {78005} \right) - {{\left( {837} \right)}^2}} \sqrt {9\left( {62449} \right) - {{\left( {745} \right)}^2}} }}\\ &= 0.341\end{aligned}\)

Thus, the correlation coefficient is 0.341.

Step 4:Conduct a hypothesis test for correlation

Definemeasure\(\rho \)as the true correlation measure for the two variables.

For testing the claim, form the hypotheses:

\(\begin{array}{l}{H_o}:\rho = 0\\{H_a}:\rho \ne 0\end{array}\)

The samplesize is9(n).

The test statistic is computed as follows:

\(\begin{aligned} t &= \frac{r}{{\sqrt {\frac{{1 - {r^2}}}{{n - 2}}} }}\\ &= \frac{{0.341}}{{\sqrt {\frac{{1 - {{\left( {0.341} \right)}^2}}}{{9 - 2}}} }}\\ &= 0.9597\\ &\approx 0.960\end{aligned}\)

Thus, the test statistic is 0.960.

The degree of freedom is calculated below:

\(\begin{aligned} df &= n - 2\\ &= 9 - 2\\ &= 7\end{aligned}\)

The p-value is computed from the t-distribution table.

\(\begin{aligned} p{\rm{ - value}} &= 2P\left( {T > 0.960} \right)\\ &= 0.369\end{aligned}\)

Thus, the p-value is 0.369.

Since thep-value is greater than 0.05, the null hypothesis fails to be rejected.

Therefore, there is not sufficient evidence to conclude the existence of a linear correlation between the counts of pleasure boats and manatee boat fatalities.