You wish to determine if there is a linear correlation between the two variables at a significance level of a = 0.01. You have the following bivariate data set. Round answers to 3 decimal places.
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- 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 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 22 39 21 38 18 23 22 79 36 42 22 65 29 Ho: p = 0 Ha: p= 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a Greater than a The p-value leads to a decision to O Reject Ho O Accept Ho O Do Not Reject Ho The conclusion is O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is a significant negative linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…You wish to determine if there is a negative 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 31 23 60 27 33 18 64 36 72 31 65 31 Ho: ρ = 0Ha: ρ < 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is insufficient evidence to make a conclusion about the 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 a significant positive linear correlation between driver age and number of driver deaths. There is a…You wish to determine if there is a positive 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 66 20 75 32 44 31 44 36 19 23 65 29 61 22 58 25 71 27 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
- The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. LOADING... Click the icon to view the table of critical values of the correlation coefficient. a) Which variable is likely the explanatory variable and which is the response variable? Critical Values for Correlation Coefficient n 3 0.997 4 0.950 5 0.878 6 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374 29 0.367 30 0.361 n (a) Which variable is likely the explanatory variable and which is the response variable? The explanatory variable is…You wish to determine if there is a positive 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 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 19 27 20 58 31 77 31 47 24 50 26 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject HoYou 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 65 27 34 27 76 24 55 34 71 21 49 24 34 36 27 19 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is a significant positive 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 a significant negative linear correlation between driver age and number of driver deaths. There is insufficient evidence to make a…
- Listed below are the amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of α=0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) 31.65 53.83 87.10 103.64 60.34 109.80 Tip (dollars) 3.74 5.76 14.73 16.86 7.44 20.73 1. The linear correlation coefficient is r= 2. What are the null and alternative hypotheses? 3. The test statistic is t= 4. The P-Value is P=The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.692. At a =0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? E Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho: p o Maximum Weights and Jump Heights Ha: p o Maximum Jump height, y Determine the critical value(s). weight, x 190 60 to = (Round to three decimal places as needed. Use a comma to separate answers as needed.) 185 56 155 55 Determine the standardized test statistic. 180 59 175 55 t= (Round to three decimal places as needed.) 170 65 What is the conclusion? 150 52 160 52 Ho. There V enough evidence at the 5% level of significance to conclude that there is a significant linear correlation between the…We give the total variation, the unexplained variation (SSE), and the least squares point estimate b1 . Total variation = 13.459; SSE = 2.806; b1 = 2.6652 Click here for the Excel Data File Using the information given, find the explained variation, the simple coefficient of determination (r2), and the simple correlation coefficient (r). Interpret r2. (Round your answers to 3 decimal places. Round your percent to 1 decimal place.) Explained variation r2 r % of the variation in demand can be explained by variation in price differential.