A magazine tested paints. The table below shows the overall quality score and cost in dollars per gallon. Use the rank correlation coefficient to test for a correlation between the two variables. Use a significance level of alpha = 0.05. Based on these results, do you get better quality paint by paying more?     A. Reject the null hypothesis that there is no correlation between quality and cost. It appears that you cannot expect to get higher quality by purchasing more expensive paint.   B. Reject the null hypothesis that there is no correlation between quality and cost. It appears that you can expect to get higher quality by purchasing more expensive paint.   C. Fail to reject the null hypothesis that there is no correlation between quality and cost. It appears that you can expect to get higher quality by purchasing more expensive paint.   D. Fail to reject the null hypothesis that there is no correlation between quality and cost. It appears that you cannot expect to get higher quality by purchasing more expensive paint.

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 64 32 55 30 72 36 34 30 31 18 16 29 21 22 32 18 46 24 46 31   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 Do Not Reject Ho Reject Ho Accept Ho   The conclusion is  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 a significant positive linear correlation between driver age and number of driver deaths. There is…

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…

A magazine tested LCD televisions. The table below shows the overall quality score and cost in hundreds of dollars. Use the rank correlation coefficient to test for a correlation between the two variables. Use a significance level of x = 0.05. Based on these results, can you expect to get higher quality by purchasing a more expensive LCD television? Quality 76 74 71 70 69 68 65 62 62 60 59 Cost 27 24 12 11 21 27 30 38 24 21 11 Click the icon to view the critical values of Spearman's rank correlation coefficient. Determine the null and alternative hypotheses for this test. Choose the correct answer below. OA. Ho: rs = 0 OB. Ho: rs #0 H₁: rs =0 H₁: rs #0 O C. Ho: Ps #0 H₁: Ps=0 Determine the correlation coefficient. 's (Round to three decimal places as needed.) Determine the critical value(s) of the correlation coefficient. D. Ho: Ps=0 H₁: Ps #0 (Round to three decimal places as needed. Use a comma to separate answers as needed.) Choose the correct answer below. O A. Fail to reject the…

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 Ho

A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below. Seeds Produced 68 56 61 Sprout Percent 60.6 69.2 = 0 48 64.7 64.6 #0 a. Find the correlation coefficient: b. The null and alternative hypotheses for correlation are: H₂: ? H₁: 2 The p-value is: 63 64.1 40 Round to 2 decimal places. 63 62 65.1 68.4 84 (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. O There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically significant…

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 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 22 20 53 25 19 30 35 23 71 26 36 21 48 25 19 28   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 Accept Ho Do Not Reject Ho Reject Ho   The conclusion is  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.…

A magazine tested paints. The table below shows the overall quality score and cost in dollars per gallon. Use the rank correlation coefficient to test for a correlation between the two variables. Use a significance level of alpha equals 0.05. Based on these​ results, do you get better quality paint by paying​ more?   a. Calculate the test statistic. r s equals  (Round to three decimal places as​ needed.)     b. Find the critical values. r s equals plus or minus ​(Round to three decimal places as​ needed.)

After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation

The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. 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. Should we expect that there would be a correlation? Use a significance level of a=0.05. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. A. 20- 20 E 70 OB. 70- 20+ 20 70 Best Actress (years) The linear correlation coefficient is r= (Round to three decimal places as nee Best Actress (years) Best Actresses and Best Actors Best Actress 28 31 30 64 31 Best Actor 44 39 37 43 49 33 46 47 56 OC. COD. Q 70- 20 20 Best Actress (years) 30 59 23 42 53 442 52 39 56 44 34 70 20 20 70 Best Actress (years)