The following data on price ($) and the overall score for 6 stereo headphones that were tested by Consumer Reports were as follows. The estimated regression equation for these data is ŷ 25.135 +0.305x. Source of Sum of Degrees Variation Squares of Freedom a. Does the t test indicate a significant relationship between price and the overall score? Compute the value of the t test statistic. Use a = 0.05 t= (to 2 decimal places.) Use Table 2 of Appendix B to find the p-value. The p-value is between 0.02 and 0.05 + What is your conclusion? Use a = 0.05. There is a significant relationship between price and overall score Regression Error Total Ⓡ b. Test for a significant relationship using the F test. Use Table 4 of Appendix B. p-value is between 0.01 and 0.025 ✔ What is your conclusion? Use a = 0.05. Because p-value is less than or equal to # 0.05, we reject Ho: B₁ is equal to zero c. Show the ANOVA table for these data. Round your answers to three decimal places, if necessary. Do not round intermediate calculations. Ⓡ Ⓡ * Mean Square Ⓡ Ⓡ Brand Bose Scullcandy Koss F Phillips/O'Neill p-value (to 4 decimals) Denon JVC Price Score 190 78 160 75 85 67 80 56 80 40 35 27

Because colas tend to replace healthier beverages and colas contain caffeine and phosphoric acid, researchers wanted to know whether cola consumption is associated with lower bone mineral density in women. The accompanying data lists the typical number of cans of cola consumed in a week and the femoral neck bone mineral density for a sample of 15 women. Complete parts (a) through (d) below. Click the icon to view the women's data. (a) Find the regression equation treating cola consumption per week as the x-variable. y=x+ (Round to three decimal places as needed.) (b) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OA. For 0 colas consumed in a week, the bone density is predicted to be (Round to three decimal places as needed.) g/cm³. OB. For every cola consumed per week, the bone density decreases by (Round to three decimal places as needed.) g/cm³, on average. OC. For a bone density of 0 g/cm³, the number of colas…

For the relationship between Calories and Carbs, here is the equation of the line of best fit: nts Regression Equation: Calories = 2.36 + 4.432 Carbs The range of Carb values in the dataset was between 17 and 47 Carbs. What wourd you say if asked to predict the number of Calories if a cereal had 60 Carbs? Type your response in the text box..

Critical Values of the Pearson Correlation Coefficientr a= 0.05 a= 0.01 NOTE: To test H, p-0 against H,: p#0, reject H, jr the absolute value of r is preater than the critical yalue in the table. 0.950 0.990 0.959 0.917 0.875 5 0.878 6 0.811 0.754 7 0.834 0.798 8 0.707 0.666 0.632 0.602 9 10 0.765 11 0.735 12 0.576 0.708 13 0.553 0.684 0.532 0.514 0.497 0.482 14 0.661 15 0.641 16 0.623 17 18 0.606 0.590 0.468 19 0.456 0.444 0.575 20 0.561 25 0.396 0.505 0.463 30 0.361 35 0.335 0.430 40 0.312 0.402 45 0.294 0.279 0.378 0.361 50 60 0.254 0.330 70 80 0.236 0.305 0.286 0.220 90 0.207 0.196 0.269 100 0.256 a= 0.05 a=0.01

Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 79 78 P Left Arm 177 170 150 148 148 Click the icon to view the critical values of the Pearson correlation coefficient r |x. (Round to one decimal place as needed.) The regression equation is y = Given that the systolic blood pressure in the right arm is 85 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed.)

The sweetness, y, of the fruit is supposed to be related to the average daily sunshine hours, x. The following data shows the sweetness of the same type of fruit at different locations (sunshine hours). Fit the data to a simple linear regression model. x: 5, 6, 7, 6, 6, 8, 7, 5. y: 9, 10, 10, 11, 12, 13, 12, 8. Predict the true mean sweetness for average daily hours of 8 hours, and calculate the residual for average daily sunshine hours of 8 hours.

Please help with this problem. Answer all parts please.

I need help finding the answers for A,B,and C

The data show the chest size and weight of several bears. Find the regression​ equation, letting chest size be the independent​ (x) variable. Then find the best predicted weight of a bear with a chest size of 40inches. Is the result close to the actual weight of 352​pounds? Use a significance level of 0.05.a. Chest size​ (inches) 41 54 44 55 39 51   Weight​ (pounds) 328  528  418  580  296  503   a.What is the regression​ equation?  b. The best predicted weight for a bear with a chest size of 39 inches is _______pounds.   ​

#a. Does the t test indicate a significant relationship between price and the overall score? Compute the value of the t test statistic. Use x=0.05