Use polynomial regression to fit a parabola to the data given below.24789.y11.524581013Which of the following most nearly gives the value of the coefficients a, b, and c?a)a = 0.19102 ;b = –0.45184 ; c = 1.48810d)a = 0.19112 ; b = –0.45137 ;c = 1.48808b)a = 0.19012 ; b = –0.45184; c = 1.48801e)a = 0.19201 ;b = -0.45137;c = 1.48180c)a = 0.19120 ;b = –0.45134;c = 1.48380f)None of the choices

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Answered: Use polynomial regression to fit a…

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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G The following table shows the weights of some persons in kilograms and their heights in centimeters: X Weight (kg) 60 70 59 90 Height (cm) 165 170 144 189 Compute the slop B1 needed for the linear regression equation. Selected Answer: Correct Answer: [None Given] 1.15 + 5%
I need help on part a.
Use the following linear regression equation to answer the questions. X3=-17.3+3.7x1+9.6x4-2.0x7 a) which number is the constant term? List the coefficient explanatory variables. constant= x1 coefficient = x4 coefficient =x7 coefficient =b) if x1=1, x4=-3, x7=5, what is the predicted value for x3?(round you answer to one decimal place.) c) suppose x1 and x7 were held at fixed but arbitrary values. If x4 increased by 1 unit what would we expect the corresponding change in x3 to be? if x4 increased by 3 units what would be the corresponding expected change in x3?if x4 decreased by 2 units what would we expect for the corresponding change in x3?
Consider the regression équation In =3.94+0.4X₁₁ +0.7X₂- a. Predict the value of Y when X₁ =7.4 and X₂ = 5.2. b. Interpret the meaning of the regression coefficients 100 b,, and 100-b₂. a. The predicted value of Y is (Type an integer or decimal rounded to two decimal places as needed.) b. Choose the correct answer below. OA. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by b, or by percent, respectively. B. Holding constant the other variables, for every one percent increase in X, or X₂, the value of Y increases by b, or b₂ percent, respectively. C. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by 100 b, or 100-b₂ percent, respectively. OD. Holding constant the other variables, for every one percent increase in X, or X₂, the value of Y increases by b, or b₂ units, respectively. OE. For every decrease of one unit of In Y, holding bo constant, the estimated change in X, or…
Solve Part F. Please and Thank You.
When debris is dropped from a cliff its height, h, measured in feet at VarlousS times ,t, measured in seconds ,s, is shown in the accompanying table. 1 2 3 4 Time(t) Height(h) 880 840 802 735 660 480 A) Using the given data, determine the Quadratic Regression Equation, rounding coefficients to the nearest thousandth. B) Using the Regression Equation, find the appropriate height, rounded to the nearest foot, of the debris at time t=7 seconds.
62.6 08 4. Show graphically the regression equations of illustration 3.
A business analyst is hired by a local real estate firm to forecast how condo sales on a quarterly basis over the next several years. The firm provides the analyst with three years worth of quarterly condo sales data. Noticing that the data exhibits increasing trend and a seasonal pattern, the analyst chooses to create a multiple regression model for generating the forecasts: y = 130 + 16 OQtr1+(-98) Qtr2 + (-85) Qtr3 + 9 t In the equation above, Qtr1, Qtr2, and Qtr3 are dummy variables corresponding to the first, second, and third quarters of the calendar year and t is the time period number, starting with t = 1 for the first quarter of year 1. %3D Using the model described above, what is the forecast for the number of condo sales the firm can expect during the second quarter of year 5? (Hint: the seeond quarter of year 5 would be time perlodt- 18.)
i. Create a quadratic model: thergh j. What is the R2 value? What does this tell you about the relationship between x and y? k. Do a scatterplot of Y1 and the data. What does that tell you about the quadratic model? 1. Store the predictions in L3 and the Residuals in L4. m. Do a scatterplot of X-values vs Residuals. When doing this plot, first Deselect Y1. Sketch the plot here. What does this tell you about the quadratic model? n. Look at the Residual plot and use the Trace Key to find the 'largest' residual (it could be positive or negative.) Go back to your Stat Editor and find the corresponding x- value, y-value and predicted y-value.
The quadratic regression equation shown below is for a sample of n=22. a. Predict Y for X1=3. (Type an integer or a decimal.)
26. For the following scores: X 3 5 2 2 4 1 4 Y 8 8 6 3 6 4 7 a. Find the regression equation for predicting Y from X. b. Calculate the predicted Y value for each X.
An automotive sales manager wishes to examine the relationship between age (years) and sales price ($) for used automobiles of a certain brand. The accompanying table contains data for a sample of a certain make and model that were listed for sale at a car shopping website. b. Fit a quadratic regression model to predict price and state the quadratic regression equation.

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