5. Use least-squares regression to fit a straight line to data given in table.Show data and line in the same graph. Give equation of the fitted line.03915175691112Xy57V(knots) 679P (kW) 170 270 400 5601286. Fit a straight line, a parabola and a cubic equation to the speed power dataof a ship. Compare your results. (use matlab, excel etc. to obtain graph andrelation)10770191411 12 13 14 151030 1360 1800 2350 31007. Estimate the first derivative the function f(x) = e* cosx, at x=2.0employing step sizes of h= 0.25. Use centered finite divided differenceformulas with 2 and 4 point. Compare your results with true value.Estimate error, &t.

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Answered: 5. Use least-squares regression to fit…

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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Q5/ Use Linear Regression to fit the following data: X 1 2 4 5 6 Y 4 10 10 9 3
Use least squares regression to fit a line to the table data below.
Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative?
give an easy example of an simple linear regression with solution and line graph
Report the equation of the regression line and interpret it in the context of the problem
Draw a graph of the least-squares regression line on your scatterplot. (For hand-drawing, round the slope and y-intercept to one decimal place before drawing the line.) Be sure to show how you were able to plot the line starting with its equation. Model City Miles per Gallon Highway Miles per Gallon Acura RLX 20 29 BMW 530i 24 34 Buick LaCrosse eAssist 25 35 Chevrolet Malibu 29 36 Ford Hybrid FWD 43 41 Honda Civic 32 42 Infiniti Q50 Red Sport 20 26 Kia Forte 30 40 Lexus ES 350 22 33 Mercedes Benz AMG S 21 30 Mini Cooper Clubman 24 32 Nissan Maxima 20 30 Suburu Legacy AWD 25 34 Toyota Prius ECO 58 53
Write out the full linear model including all dummy variables below. Don’t worry about estimating regression coefficients just yet. Feel free to abbreviate variable names so long as they are clearly distinguishable.
A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. Time 10 8 6 13 19 18 27 10 7 Money 58 25 41 51 84 81 87 45 15 1. The equation of the linear regression line is: ˆyy^ = ______ +_____ xx (Please show your answers to two decimal places)
Data were collected that included information on the weight of the trash (in pounds) on the street one week and the number of people who live in the house. The figure shows a scatterplot with the regression line. Complete parts (a) through (d) below.
9 students were surveyed to see what their age is and what their income level is. Find the equation of the line using linear regression. We want to predict their age using their income. age 18 24 38 22 19 35 28 19 27 income 456 786 835 855 645 244 587 1400 975 Just a side note, the 19 year old is making 1400, would be considered an outlier since they are making way more than everyone else. (y=-.0061x+34.9874 4 decimals) y=30.3709-.0064
Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
Please answer letters b-e.

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5. Use least-squares regression to fit a straight line to data given in table. Show data and line in the same graph. Give equation of the fitted line. 0 3 5 9 15 17 5 6 7 9 11 12 X y 12 8 19 14