A magazine publishes restaurant ratings for various locations around the world. The magazine rates the restaurants for food, decor, service, and the cost per person. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the three ratings. The magazine has compiled the accompanying table of this summated ratings variable and the cost per person for 25 restaurants in a major city. Complete parts (a) through (e) below. Click the icon to view the table of summated ratings and cost per person. a. Construct a scatter plot. Choose the correct graph below. OA A Cost (5) 90+ ********** hata Rating 90 Q OB. A Cost (3) 90+ Rating Q b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients bo and b₁. bo=and b₁ = (Round to two decimal places as needed.) OC. A Cost (5) 90+ Rating Summated Ratings and Cost Per Person Summated Rating Cost (5 per person) 40 48 60 61 42 40 43 43 55 67 69 66 63 61 55 61 50 48 53 51 75 63 55 51 57 46 57 54 67 63 52 74 69 Print 35 35 37 85 51 39 33 31 23 43 46 59 27 49 49 Done X

Refer to the data set:Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 5.

Can you please tell also the test statistics and if the weight is close to 518 pounds?

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y=-59.97x+67.54 and the r=-0.31 What percentage of the variation in y can be explained by the variation in the values of x? r² = %           (Report exact answer, and do not enter the % sign) .

The number of megapixels in a digital camera is one of the most important factors in determining picture quality. But, do digital cameras with more megapixels cost more? The following data show the number of megapixels and the price ($) for 10 digital cameras(Consumer Reports, March 2009). Use these data to develop an estimated regression equation that can be used to predict the price of a digital camera given the number of megapixels. Brand and Model Megapixels Price (S) Canon PowerShot SD1100 IS Casio Exilim Card EX-510 8 180 200 230 10 Sony Cyber-shot DSC-T70 Pentax Optio M50 Canon PowerShot G10 120 470 15 8 Canon PowerShot A590 IS Canon PowerShot El 140 180 10 12 Fujifilm FinePix FOOFD Sony Cyber-shot DSC-W170 Canon PowerShot A470 310 10 250 110

-by-Side We expect a car's highway gas milcage to be related to its city gas mileage (in miles per gallon, mpg). Data for all 1259 vehicles in the government's 2019 Fuel Ecomomy Guide give the regression line (b) What is the intercept? Give your answer to three decimal places. highway mpg - 8.720 + (0.914 x city mpg) intercept: mpg for predicting highway milcage from city mileage. Why is the value of the intercept not statistically meaningful? O The value of the intercept represents the predicted highway milcage for city gas mileage of 0 mpg. and such a prodiction would be invalid since O is outside the range of the data. O The value of the intercept represents the predicted city mileage for highway gas mileage of 0 mpg. and such a car does not exist. The value of the intercept is an average value calculated from a sample. The value of the intercept represents the predicted highway milcage for slope 0.

The following data show the brand, price (S), 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 ý = 22.522 + 0.335x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 78 B 150 73 95 63 70 58 E 70 38 35 26 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = (b) Compute the coefficient of determination rt. (Round your answer to three decimal places.) 12 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O 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. O The least squares line did not provide a good fit as a small proportion of the variability in y…

lecture(11.12): A large amount of scatter in a scatter plot is an indication that the relationship between the two variables is (a) negative (b) strong (c) weak (d) moderate (e) positive

Pls help ASAP

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 48 inches. Is the result close to the actual weight of 538 ​pounds? Use a significance level of 0.05.