**Title: Analyzing Linear Correlation Between Driver Age and Number of Driver Deaths**You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places.| Driver Age | Number of Driver Deaths per 100,000 ||------------|--------------------------------------|| 69 | 22 || 48 | 34 || 37 | 23 || 47 | 28 || 27 | 20 || 62 | 33 || 64 | 33 |**Hypotheses:**- Ho: ρ = 0- Ha: ρ ≠ 0**Tasks:**1. **Find the Linear Correlation Coefficient (r):** - Calculate the correlation coefficient using the given data to assess the strength and direction of the linear relationship.2. **Find the p-value:** - Determine the p-value to evaluate the statistical significance of the correlation.**Decision Making:**- Compare the p-value with the significance level (α = 0.01). - The p-value is: - Greater than α - Less than (or equal to) α- The p-value leads to a decision to: - Do Not Reject Ho - Accept Ho - Reject Ho**Conclusion:**Based on the analysis, select the correct conclusion:- There is a significant negative linear correlation between driver age and number of driver deaths.- There is a significant linear correlation between driver age and number of driver deaths.- There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths.- There is a significant positive linear correlation between driver age and number of driver deaths.

The total number of pairs of observations is n = 8.Suppose the Driver Age is defined as x and the number of Driver Deaths per 100,000 is defined as y.Suppose ρ is the population correlation coefficient and r is the sample correlation coefficient between x and y.Consider the below table.xyx2y2xy652242254841430692247614841518483423041156163237231369529851492824017841372272072940054062333844108920466433409610892112Σx = 421 Σy = 215Σx2 = 23729 Σy2 = 6015 Σxy = 11501 The correlation coefficient between two variables x and y for sample size n is:The correlation coefficient is, The linear correlation coefficient is, r = 0.3057.It is needed to check whether there is a linear correlation between the age of a driver and the number of driver deaths.The null and alternative hypotheses are:H0: ρ = 0H1: ρ ≠ 0The test is both tailed.The test statistic is, Thus, the test statistic is 0.7865.The sample size is n = 8 and the degrees of freedom is, df = n – 2 = 8 – 2 = 6.Using the Excel formula =T.DIST.2T(0.7865,6), the p-value is obtained as approximately 0.4615.The excel output is,The p-value is 0.4615.The level of significance is α = 0.01.Decision rule:If p-value is less than or equal to the level of significance, reject the null hypothesis.Otherwise, fail to reject the null hypothesis.Conclusion:The p-value is greater than α.The p-value leads to a decision to do not reject H0.The conclusion is, “There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths.”.The linear correlation coefficient is, r = 0.3057.The p-value is 0.4615.The p-value is greater than α.The p-value leads to a decision to do not reject H0.The conclusion is, “There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths.”.