4:03HelpQuestionFind the linear regression line for the following tableof values. You will need to use a calculator,spreadsheet, or statistical software. Then, use theequation to estimate the value of y when x is 8.(• Round the values of a and b in the regressionequation to the nearest hundredth, then usethe equation to solve for y when x = 8. Roundthe final answer to the nearest hundredth, ifnecessary.X1234knewton.com567y4.59Provide your answer below:4.996.747.728.9210.1710.37Copy to Clipboardil 5GOpenSUI

We need to determine the linear regression line for the given table of values. We need to calculate…

Answered: Find the linear regression line for the…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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you take a bar of soap and weigh it after each shower. will the regression line be positive or negative
A snack company is preparing two mixtures of snacks from a supply of 110 pounds pretzels, 30 pounds pistachios, 10 pounds cheese puffs, 60 pounds sesame sticks, and 20 pounds toffee bites. Mixture X contains 55% pretzels, 20% pistachios, 5% cheese puffs, 20% sesame sticks, and no toffee bites, and sells for $7.99 per pound. Mixture Y contains 45% pretzels, 10% pistachios, no cheese puffs, 10 % sesame sticks, and 15% toffee bites, and sells for $5.99 per pound. If x = # of pounds of Snack X and y = # of pounds of Snack Y, determine the constraints on this linear programming problem. Inequality for pretzels [ Choose ] Inequality for pistachios ( Choose] Inequality for cheese puffs ( Choose ) Inequality for sesame sticks [Choose ] Inequality for toffee bits [ Choose ) Non-negativity inequalities [ Choose ] >
For the data in the table, find the regression equation. Here, x gives the number of calories in a hot dog, and y is the number of mg of sodium. Round the slope and y-intercept to two decima below. hen use your equation to answer the question Calories Sodium(mg) 100 311 110 304 120 308 130 337 140 320 160 341 170 375 180 353 190 362 200 372 Every extra 10 calories would be expected to add how many mg of sodium? Submit Question
A table of data points is given below. a. Find the regression equation for the data points. Use the formulas Sxx=∑ xi−x2 and Sxy=∑ xi−x yi−y to obtain Sxx and Sxy. b. Graph the regression equation and data points. x 1 2 3 y 6 5 10 a. The regression equation is y= + () x. (Simplify your answers. Type integers or decimals. Do not round.)
Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.
Use the data below for the PHONES questions that follow. Data compiled from the CIA World Factbook, https://www.cia.gov/. The number of cell phones in use in a country can be approximated from the number of main lines in use in that country by using the regression equation yhat=25+3x which had an R² of about 90%. (The numbers here are millions. For example, "1.2" would represent 1.2 million or 1,200,000.) PHONES 1 At the time the data was collected, the USA had about 314 million cell phones in use and about 150 million main lines in use. What was the residual for the USA? Enter a number of millions. For example, if your answer is 2.85 million enter "2.85". Do not enter anything else such as symbols or words.
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
Choose the correct answer of each number. 1. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales before in that branch is a. $417,750 b. $341,250 c. $376,700 d. $335,6502. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If…
We run the following regression using a sample of 148 women living in the western states. The variable wage is the hourly wage ( in USD) and educ is the number of years of education completed. wage = -3.07 + 1.52 educ Which statement best described the estimated slope coefficient? Group of answer choices A 1.52 extra years of education is predicted to increase wage by 1 USD An extra year of education is predicted to increase hourly wage by 1.52 USD A 1 percent increase in education is predicted to increase wage by 1.52 percent A 1.52 percent increase in education is predicted to increase wage by 1
Use the given data set to answer parts (a) and (b). a. Find the regression equation for the data points. X 5 b. Graph the regression equation and the data points. y -1 10 -10 y B. 10 -10- C. a. Find the regression equation for the data points. ŷ-0 (Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) b. Graph the regression equation and the data points. O A. 10 T -10- 1 2 -1 3 327 D. -10 4 y 4 28 0
For the data in the table, find the regression equation and then use it to answer the questions below. Here, x gives the number of years of experience for nurses, and y is their annual salary (in $1000's). Round the slope and y-intercept to two decimals, then do not round your answer. Years of Salary Experience ($1000's) 2 41 4 45 8 51 9. 52 12 53 14 54 16 55 18 56 19 57 25 60 a. What is the predicted salary (in $1000's) for a nurse with 33 years of work experience? b. Is your answer to part (a) an extrapolation? O No: the value of x is within the range of the data, so the prediction is meaningful O Yes: the value of x is outside the range of data, so the prediction may not be meaningful Submit Question
Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary.

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