3. The data points given below are known to fit the following type of equation: y = mx"Use a transformation to linearize this equation and then use linear regression to estimate m and n.Xy38m =415• Write clearly and legibly. Show all details of your work. Use four significant figuresin your calculations.Write your final result in the box below:n=525

The linear regression is used to fit a dataset into a linear equation of the form: y=a+bx, where a,…

Answered: 3. The data points given below are…

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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Use linear regression on your calculator to find the equation of the linear function that best fits this data. 1 3 4 5 6 y 84 110 139 170 180 222 = mx + b. Round all numbers to 2 decimal Hint: Write your final answer as an equation in the form y places.
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.)
(please solve within 15 minutes I will give thumbs up)
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
please help me answer this for my data analysis class
Consider the following regression equation: y = -3.9 + 7.2x What does 7.2 depict in the regression equation above? a) The direction of the line. b) The y-intercept. c) The point where x = 0. d) The y when x = 7.2.
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 = 1.5.
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
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
What is the linear equation (y = mx + b form) that best approximates the relationship between advertising dollars spent(x) and sales revenue(y) based on the above 8 months of data? (round to 2 decimals for the slope and the y intercept)
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.8 + 0.3x, +4.5x,, where x, is the tree's height (in feet) and x, is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. x, = 70, x, = 8.6 The predicted volume is cubic feet. (Round to one decimal place as needed.)
The data point height=175 cm, height =80 cm was misrecorded as height=145 cm, height =80 cm. If we use the simple linear regression and do not correct the mistake, what is the impact of this point on the model?

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