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? Quality 67 Cost 27 76 68 63 65 61 79 76 62 60 66 28 30 24 22 18 27 24 20 18 22 OA. 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. OB. 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. OC. 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. OD. 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.

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 48 27 38 32 57 23 43 22 43 32 38 36 72 19   Ho: ρ = 0Ha: ρ < 0 Find the Linear Correlation Coefficient    r =  Find the p-value   p-value =    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 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.

Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant negative linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places. Advertising Cost Profit 3 24 4 23 5 20 6 23 7 23 8 19 9 19 10 26   Ho: ρ = 0Ha: ρ < 0 Find the Linear Correlation Coefficient    r =  Find the p-value   p-value =

A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below.   Time 17 18 6 20 28 16 20 Money 50 55 37 79 97 60 76   Find the correlation coefficient:  r=r= Correct   Round to 2 decimal places. The null and alternative hypotheses for correlation are:H0:H0: ? μ ρ r Correct == 0H1:H1: ? μ r ρ Correct  ≠≠ 0    The p-value is:  Correct  (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically insignificant evidence to conclude that a customer who spends more time at the store will spend more money than a customer who spends less time at the store. There is statistically significant evidence to conclude that there is a correlation between the amount of time customers spend at the store and the amount of…