You wish to determine if there is a linear correlation between the two variables at a significance level of α=0.001. You have the following bivariate data set. x y 57.7 13.1 81.1 -338.4 86.1 483.1 79.9 273.1 62.9 111 62.1 222.2 126.5 189.9 70.9 364.1 73 -200.1 64.1 173.7 89.5 -194.4 75.8 17.1 95.4 177.2 63.3 79.7 71 31.2 74.3 366.7 77.9 -163.3 72.9 -555.7 41.4 43.8 What is the correlation coefficient for this data set? r = What is the p-value for this correlation coefficient? p-value = Your final conclusion is that... There is insufficient sample evidence to support the claim that there is a correlation between the two variables. There is sufficient sample evidence to support the claim that there is a statistically significant correlation between the two variables. Note: Round answers to three decimal places.
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You wish to determine if there is a linear correlation between the two variables at a significance level of α=0.01α=0.01. You have the following bivariate data set. x y 43.5 15.5 31.7 -8 50 4.3 48.9 9.4 64.2 17.8 40.6 4.2 69.9 17.3 65.8 30.7 74.1 29.3 65.5 43.8 58.5 34.2 64.9 27.8 What is the critival value for this hypothesis test?rc.v. = What is the correlation coefficient for this data set?r = Your final conclusion is that... There is insufficient sample evidence to support the claim the there is a correlation between the two variables. There is sufficient sample evidence to support the claim that there is a statistically significant correlation between the two variables. Note: In your calculations, round both r and t to 3 decimal places in ALL calculations.
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You wish to determine if there is a linear correlation between the two variables at a significance level of α = 0.05. You have the following bivariate data set: x y 57 -16.4 41 30.9 49.2 67.4 45.7 31.4 49 41.3 45.2 85.5 78.3 -1.2 What is the critival value for this hypothesis test? r_cv = What is the correlation coefficient for this data set? r = 0.595 Your final conclusion is that... There is insufficient sample evidence to support the claim the there is a correlation between the two variables. There is sufficient sample evidence to support the claim that there is a statistically significant correlation between the two variables. Note: In your calculations, round both r and t to 3 decimal places in ALL calculations.
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Use a scatterplot and the linear correlation coefficient r to determine whether there is a correlation between the two variables. (Note: Use software, and don't forget to look at the scatterplot!) (a) r = (b) There is A. a positive correlation between x and y B. a perfect positive correlation between x and y C. a negative correlation between x and y D. no correlation between x and y E. a nonlinear correlation between x and y F. a perfect negative correlation between x and y
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