You may need to use the appropriate technology to answer this question. Consider the following data on price ($) and the overall score for six stereo headphones tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest).

Consider the following data on price ($) and the overall score for six stereo headphones tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). Brand Price ($) Score A 180 78 B 150 73 C 95 63 D 70 58 E 70 40 F 35 24 (a) The estimated regression equation for this data is  ŷ = 22.054 + 0.339x,  where x = price ($) and y = overall score. Does the t test indicate a significant relationship between price and the overall score? Use ? = 0.05. State the null and alternative hypotheses.?? -H0: ?0 = 0Ha: ?0 ≠ 0 -H0: ?1 = 0Ha: ?1 ≠ 0     -H0: ?0 ≠ 0Ha: ?0 = 0 -H0: ?1 ≠ 0Ha: ?1 = 0 -H0: ?1 ≥ 0Ha: ?1 < 0 Find the value of the test statistic. (Round your answer to three decimal places.) test statistic=?? Find the p-value. (Round your answer to four decimal places.) p-value = ?? What is your conclusion? -Do not reject H0. We conclude that the relationship between…

The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration. GPA 2.6 3.4 3.6 3.2 3.5 2.9 Monthly Salary ($) 3,500 3,900 4,200 3,800 4,200 3,900 The estimated regression equation for these data is ý = 1,970.72 + 608.11x and MSE = 18,671.17. (a) Develop a point estimate of the starting salary (in dollars) for a student with a GPA of 3.1. (Round your answer to the nearest cent). (b) Develop a 95% confidence interval for the mean starting salary (in dollars) for all students with a 3.1 GPA. (Round your answers to the nearest cent). to $ (c) Develop a 95% prediction interval (in dollars) for Ryan Dailey, a student with a GPA of 3.1. (Round your answers to the nearest cent). to $

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 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)

According to Thomson Financial, last year the majority of companies reporting profits had beaten estimates. A sample of 162 companies showed that 114 beat estimates, 29 matched estimates, and 19 fell short.   (a) What is the point estimate of the proportion that fell short of estimates? If required, round your answer to four decimal places.   pshort =  (b) Determine the margin of error and provide a 95% confidence interval for the proportion that beat estimates. If required, round your answer to four decimal places.   ME =  (c) How large a sample is needed if the desired margin of error is 0.05? If required, round your answer to the next integer.   n* =

The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 22.391 + 0.326x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 71 C 95 63 D 70 56 E 70 40 F 35 24   #1) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE =   #2) Compute the coefficient of determination r2.(Round your answer to three decimal places.) r2 =   #2a) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) A) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. B) The least squares line provided a good fit as a large…

Is there a relationship between the weight and price of a mountain​ bike? The following data set gives the weights and prices for ten mountain bikes. Let the expanatory variable x be the weight in pounds and the response variable y be the​ bike's price.   Weight​ (LB) 32 33 29 29 34 37 28 30 34 30   Price​ ($) 980 350 430 710 930 160 590 530 180 1090     a. Construct a scatterplot. Interpret. b. Find the regression equation. Interpret the slope in context. Does the​ y-intercept have contextual​ meaning? c. You decide to purchase a mountain bike that weighs 33 pounds. What is the predicted price for the​ bike? a. Which scatterplot below correctly shows the​ data?     A.       254001200xy         A coordinate system has a horizontal x-axis labeled from 25 to 40 in increments of 1 and a vertical y-axis labeled from 0 to 1200 in increments of 50. A cluster of plotted points that form a line that falls from left to…

PLEASE ANSWER 4,5 AND 6

The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is  ŷ = 21.592 + 0.324x,  where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 69 C 95 61 D 70 56 E 70 38 F 35 24 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.)   (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)