Problem 1The pH in a reactor varies sinusoidally over the course of a day. Use least-squaresregression to fit a periodic equation (similar to the one given below) to thefollowing data. Use your fit to determine the mean, amplitude, and time ofmaximum pH. Note that the period is 24 hr.y = A + A₁ cos(@ot) + B₁ sin(wot)2 4 57 8.5 12 15 20 22 247.3 7 7.1 6.5 7.4 7.2 8.9 8.8 8.9 7.9 7Time, hr| OpHDevelop a Pseudocode for the calculations. Plot your fit along with thedata.

Given the data, tpH07.32747.156.577.48.57.2128.9158.8208.9227.9247We need to fit the curve .The…

Answered: Problem 1 The pH in a reactor varies…

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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The accompanying table provides data for tar, nicotine, and carbon monoxide (CO) contents in a certain brand of cigarette. Find the best regression equation for predicting the amount of nicotine in a cigarette. Why is it best? Is the best regression equation a good regression equation for predicting the nicotine content? Why or why not? Tar Nicotine CO4 0.5 416 1.0 1817 1.1 1813 0.7 1713 0.7 1814 0.9 1415 1.1 1615 1.2 1615 1.2 149 0.7 1214 0.7 1813 0.8 1813 0.8 1915 1.1 162 0.2 314 1.1 1715 0.9 1514 0.8 1814 1.1 1614 0.9 1716 1.1 1414 1.0 167 0.6 717 1.3 1514 1.1 14
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Please give a step-by-step solution. Answer question 4.
Question 4 The following table of values gives a company's annual profits in millions of dollars. Rescale the data so that the year 2003 corresponds to x = 0. b) 0.0143 c) 0.3786 d) 0.3286 e) 0.5214 Year f) None of the above 2003 Profits (in millions of dollars) 17.1 2004 2005 2006 Find the cubic regression model for the data. Which of these is the coefficient of the x² term of the cubic regression model? a) ○ 1.1143 2007 2008 16.8 15.9 17.1 17.3 18.4 Review Later
question 1
Question 3. Plot the voltage as a function of time and use Newton's divided difference method to compute the voltage at t=3.145 sec from the following experimental data: t(sec) 2 4 V(Volt) 9.4 7.31 5.15 3.55 2.81 2.04 Solution:
P QUESTION 2 The value V of a piece of equipment between 1990 and 1995 is given in the table. Let t represent the year with t = 0 corresponding to 1990. Find the regression equation for the data in the table: Time, t 0 Value, V ($) 500 O y = 514.770(0.8x O y = -50x + 500 Oy=-x2 - 50x + 500 O y = 50x + 500 QUESTION 3 1 2 3 4 5 450 400 350 400 350 300 250 The table gives the average heights of children for ages 1-10, where x = the age (in years) and y = the height (in cm). 3 4 5 6 7 8 9 10 1 Age (years) Click Save and Submit to save and submit. Click Save All Answers to save all answers. 2 E; M 64 Save All Answer
QUESTION 18 Given the following information Ex = 64222 , Exy= 64346 n = 12, Ey = 876 , Ey=65850, Ex=854 , The slope of the regression line of y on x is: 1.151 0.6222 0.5816 0.4968 Click Save and Submit to save and submit. Click Save All Answers to save all answers.
Determine the equation of the sinusoidal regression function for the following data. 10 15 20 25 30 120 138 122 105 121 140 125 Using your regression equation, what is the value of y, to the nearest tenth, if x = 45? %3D A
Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file Week 4 Assignment Chapter 12 Problem 64. Use regression to fit the following model to these data:Yt = a + b1Yt−1 + b2Pt + etThis equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term. If the price of a portrait during month 21 is $10, what would you predict for sales in month 21? Sales Price $400,000 $15 $1,042,000 $12 $1,129,000 $24 $1,110,000 $18 $1,336,000 $18 $1,363,000 $30 $1,177,000 $27 $603,000 $24 $582,000 $36 $697,000 $27 $586,000 $24 $673,000 $27 $546,000 $30 $334,000 $33 $27,000 $24 $76,000 $27 $298,000 $30 $746,000 $18 $962,000 $21 $907,000 $24
The accompanying table provides data for tar, nicotine, and carbon monoxide (CO) contents in a certain brand of cigarette. Find the best regression equation for predicting the amount of nicotine in a cigarette. Why is it best? Is the best regression equation a good regression equation for predicting the nicotine content? Why or why not? Tar Nicotine CO4 0.5 415 1.0 1916 1.1 1714 0.9 1713 0.7 1815 1.1 1315 1.1 1715 1.1 1614 1.0 169 0.7 1313 0.7 1813 0.7 1813 0.8 1714 1.0…

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