Question

Question Help 3.3.9 The Minitab output shown below was obtained by using paired data consisting of weights (in b) of 29 cars and their highway fuel consumption amounts (in migal). Along with the paired sample data, Minitab was also given a car weight of 3000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 29 pairs of data, in there sufficient evidence to support a daim of linear correlation between the weights of cars and their highway fuel consumption amounts? Cick the icon to view the Minitab display. The linear correlation coefficient in Minitab output (Round to three decimal places as needed.) The regression equation is Highway - 50.5 -0.00501 Weight Predictor Constant Weight Coef 50.465 -0.0050096 SE Coel 2883 0.0007962 т 17.15 -7.79 Р 0.000 0.000 S2.27863 R-Sq64.4% R-Sqladi) - 61.7% Predicted Values for New Observations New Obs Fit 35.436 SE FI 0.499 95% CI (34.435, 36.437) 95% PI (30.846, 40.027) 1 Values of Predictors for New Observations New Enter your answer in the answer box and then click Check Answer Obs 1 Weight 3000 Check Answer 1 part remaining Show All X 116764238 58.00 710908578 213.pg media_950_95.00 119908578_213.jpg media_950 96.png MacBook Pro 30 F 888 M 542 esc 52 199 FO FO FE $ A + 4 3 % 5 & 7 o 1 2 4 6 8 delete 9 سی O Q W E R Y T I P اس اسيا ] 20 A S D F G H J K L ick < > ? Z X C Y B N M

Answer 1

Linear correlation coefficient =

= V0.644 = +0.802

To decide the sign of correlation coefficient , we consider the sign of slope.

Coefficient for weight = - 0.0050096

which is negative.

Hence,

Linear correlation coefficient = - 0.802