The correlation coefficient r is a sample statistic. What does it tell us about the value of the population correlation coefficient p (Greek letter rho)? You do not know how to build the formal structure of hypothesis tests of p yet. However, there is a quick way to determine if the sample evidence based on p is strong enough to conclude that there is some population correlation between the variables. In other words, we can use the value of r to determine if p + 0. We do this by comparing the value Ir| to an entry in the correlation table. The value of a in the table gives us the probability of concluding that p +0 when, in fact, p = 0 and there is no population correlation. We have two choices for a: a = 0.05 or a = 0.01. Critical Values for Correlation Coefficientr a = 0.05 a- 0.01 na= 0.05 a- 0.01 a= 0.05 a- 0.01 3 1.00 1.00 13 0.53 0.68 23 0.41 0.53 4 0.95 0.99 14 0.53 0.66 24 0.40 0.52 0.88 0.96 15 0.51 0.64 25 0.40 0.51 6 0.81 0.92 16 0.50 0.61 26 0.39 0.50 7 0.75 0.87 17 0.48 0.61 27 0.38 0.49 8 0.71 0.83 18 0.47 0.59 28 0.37 0.48 9. 0.67 0.80 19 0.46 0.58 29 0.37 0.47 10 0.63 0.76 20 0.44 0.56 30 0.36 0.46 11 0.60 0,73 21 0.43 0.55 12 0.58 0.71 22 0.42 0.54 (a) Look at the data below regarding the variables x = age of a Shetland pony and y = weight of that pony. Is the value of Ir| large enough to conclude that weight and age of Shetland ponies are correlated? Use a = 0.05. (Round your answer for r to four decimal places.) 6. 95 12 17 20 y 60 140 170 190 n USE SALT critical r Conclusion O Reject the null hypothesis, there is sufficient evidence to show that age and weight of Shetland ponies are correlated. O Reject the null hypothesis, there is insufficient evidence to show that age and weight of Shetland ponies are correlated. O Fail to reject the null hypothesis, there is insufficient evidence to show that age and weight of Shetland ponies are correlated. Fail to reject the null hypothesis, there is sufficient evidence to show that age and weight of Shetland ponies are correlated. (b) Look at the data below regarding the variables x = lowest barometric pressure as a cyclone approaches and y = maximum wind speed of the cyclone. Is the value of Ir| large enough to conclude that lowest barometric pressure and wind speed of a cyclone are correlated? Use a = 0.01. (Round your answer for r to four decimal places.) 975 926 149 1004 992 935 980 |y] 40 74 100 65 145 critical r Conclusion O Reject the null hypothesis, there is sufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated. O Reject the null hypothesis, there is insufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated. O Fail to reject the null hypothesis, there is insufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated. O Fail to reject the null hypothesis, there is sufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated.

The correlation coefficient r is a sample statistic. What does it tell us about the value of the population correlation coefficient p (Greek letter rho)? You do not know how to build the formal structure of hypothesis tests of p yet. However, there is a quick way to determine if the sample evidence based on p is strong enough to conclude that there is some population correlation between the variables. In other words, we can use the value of r to determine if p + 0. We do this by comparing the value Ir| to an entry in the correlation table. The value of a in the table gives us the probability of concluding that p +0 when, in fact, p = 0 and there is no population correlation. We have two choices for a: a = 0.05 or a = 0.01. Critical Values for Correlation Coefficientr a = 0.05 a- 0.01 na= 0.05 a- 0.01 a= 0.05 a- 0.01 3 1.00 1.00 13 0.53 0.68 23 0.41 0.53 4 0.95 0.99 14 0.53 0.66 24 0.40 0.52 0.88 0.96 15 0.51 0.64 25 0.40 0.51 6 0.81 0.92 16 0.50 0.61 26 0.39 0.50 7 0.75 0.87 17 0.48 0.61 27 0.38 0.49 8 0.71 0.83 18 0.47 0.59 28 0.37 0.48 9. 0.67 0.80 19 0.46 0.58 29 0.37 0.47 10 0.63 0.76 20 0.44 0.56 30 0.36 0.46 11 0.60 0,73 21 0.43 0.55 12 0.58 0.71 22 0.42 0.54 (a) Look at the data below regarding the variables x = age of a Shetland pony and y = weight of that pony. Is the value of Ir| large enough to conclude that weight and age of Shetland ponies are correlated? Use a = 0.05. (Round your answer for r to four decimal places.) 6. 95 12 17 20 y 60 140 170 190 n USE SALT critical r Conclusion O Reject the null hypothesis, there is sufficient evidence to show that age and weight of Shetland ponies are correlated. O Reject the null hypothesis, there is insufficient evidence to show that age and weight of Shetland ponies are correlated. O Fail to reject the null hypothesis, there is insufficient evidence to show that age and weight of Shetland ponies are correlated. Fail to reject the null hypothesis, there is sufficient evidence to show that age and weight of Shetland ponies are correlated. (b) Look at the data below regarding the variables x = lowest barometric pressure as a cyclone approaches and y = maximum wind speed of the cyclone. Is the value of Ir| large enough to conclude that lowest barometric pressure and wind speed of a cyclone are correlated? Use a = 0.01. (Round your answer for r to four decimal places.) 975 926 149 1004 992 935 980 |y] 40 74 100 65 145 critical r Conclusion O Reject the null hypothesis, there is sufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated. O Reject the null hypothesis, there is insufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated. O Fail to reject the null hypothesis, there is insufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated. O Fail to reject the null hypothesis, there is sufficient evidence to show that lowest barometric pressure and maximum wind speed for cyclones are correlated.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section: Chapter Questions

Problem 8SGR

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