Consider the table of data below.xy1.20.91.72.42.83.24.55.195.210 5.412Y3=4a) Use Desmos (watch Video if you need help) to find the equation of the least squares(regression) line. Round to 2 decimal places as needed.5678Important reminder: when entering equations for Desmos to approximate, remember touse "-" instead of "="b) Find the R²-value. Round to 4 decimal places as needed.R² ==Question Help: VideoSubmit Question

Answered: Image /qna-images/answer/38990324-b4a0-401d-9692-aaef32fbfa22.jpg

Answered: Consider the table of data below. x y…

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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An experiment is run. The mass of an object is recorded over time. Time (min) Mass (g) 32 40 36 32 37 32 39 30 50 27 Using your calculator, run a linear regression to determine the equation of the line of best fit. Round to two decimal places, use x for the variable.y=Using your equation, estimate the mass of the object at 41 minutes.grams=
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.)
An instructor asked a random sample of eight students to record their study times at the beginning of a course. She then made a table for total hours studied (x) over 2 weeks and test score (y) at the end of the 2 weeks. The table is given below. Complete parts (a) through (f). x 10 13 10 18 6 15 16 21 y 93 79 81 74 85 81 85 80 a. Find the regression equation for the data points. b. Graph the regresson equation c. Describe the apparent relationship between the two variables. d. Identify the predictor and response variables. e. Identify outliers and potential influential observations. f.Predict the score for a student that studies for 17 hours.
The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.940x + 34. 128. Find the coefficient of determination and interpret the result. 785.8 784.5 1032.7 963.8 1211.5 Money raised, x Money spent, y 456.6 654.6 733.8 449.4 691.4 734.6 764.4 739.3 1018.6 930.3 1172.9 Find the coefficient of determination and interpret the result. 2 = 0.989 (Round to hree decimal places as needed.)
Use the data in the table below to complete parts (a) through (d). x 37 34 40 46 42 50 62 56 51 y 22 20 25 32 27 30 30 25 28 Find the equation of the regression line. y=
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 63 inches. Is the result close to the actual weight of 522 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 D 414 312 499 450 456 260 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 522 pounds? O A. This result is not very close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is close to the actual weight of the…
Use the given data to find the scatter plot, equation of the regression line, and prediction. 4) Managers rate employees according to job performance and attitude. The results for several randomly selected employees are given below. Performance 59 63 65 69 58 77 76 | 69 70 64 Attitude 72 67 78 82 75 87 92 83 87 78 What function do you use to see the scatterplot on the calculator. Scatterplot from the calculator:
The table shows the total square footage (in billions) of retailing space at shopping centers and their sales (in billions of dollars) for 10 years. The equation of the regression line is y = 516.388x - 1699.161. Complete parts a and b. Total Square Footage, X Sales, y 4.9 5.1 5.2 5.4 5.6 5.7 ********** (a) Find the coefficient of determination and interpret the result. 5.9 5.8 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? 5.9 883.3 937.6 986.3 1059.5 1107.2 1200.9 1281.1 1340.8 1438.2 1536. 6.2 OA. The coefficient of determination is the fraction of the variation in sales that can be explained by the variation in total square footage. The remaining fraction of the variation is unexplained and is due to other factors or to sampling error. OB. The coefficient of determination is the fraction of the variation in sales that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation is…
The table shows the lengths and weights of seven muskies captured by the Department of Natural Resources in Catfish Lake in Eagle River, Wisconsin. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. Musky 1 2 3 4 5 6 7 Length (in.) 26 27 29 33 35 36 38 Weight (lb) 5 8 9 12 14 14 19
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.493x - 83.403. Complete parts (a) and (b) below. A Average Weekly Wages (state), x Average Weekly Wages (federal), y 764 1003 766 1048 791 1119 (a) Find the coefficient of determination and interpret the result. r² = 0 (Round to three decimal places as needed.) 800 1152 843 1201 887 1250 924 1277 939 1306
Use the data in the table below to complete parts (a) through (d). 39 33 40 47 42 50 59 56 51 24 22 27 32 30 31 31 27 29 Click the icon to view details on how to construct and interpret residual plots. (a) Find the equation of the regression line. (Round to three decimal places as needed.) (b) Construct a scatter plot of the data and draw the regression line. Plot the x-values on the horizontal axis and the y-values on the vertical axis. Choose the correct graph below. OA. В. Oc. OD. 34 70, (c) Construct a residual plot. Plot the x-values on the horizontal axis and the residuals on the vertical axis. Choose the correct graph below. O A. Ов. Oc. OD. (d) Determine if there are any patterns in the residual plot and explain what they suggest about the relationship between the variables. The residual plot a pattern because the residuals about 0. This implies the regression line a good representation of the relationship between the variables.
The following data is given: x -2 -1 0 1 2 y 1.5 3.2 4.5 3.4 2 Determine the coefficients a and b in the function y=a/(x2+b) that best fit the data. (Write the function in a linear form, and use linear least-squares regression to determine the value of the coefficients.) Once the coefficients are determined make a plot that shows the function and the data points.

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