se Schedule Mid Micin Bonus Homework 8.5 Logistic XJ PeusedJared Sharpelag questionRound answers to two decimal places.A study is done on the amount of electricity produced y in billions of kWh by nuclear power x years after the year 1956. (x = 0means 1956). The study yielded the following logistic regression model.810y = +15420e-1.003zWhat would this model predict the amount of electricity to be in the year 1961?Electricity would bebillion kWhWhat would this model predict the amount of electricity to be in the year 1967?Electricity would bebillion kWhWhat would this model predict the amount of electricity to be in the year 1977?Electricity would bebillion kWh447 PMP.44°F(2612/15/2021bomeendpg uport scdeletefhonumlockbackspace67898home5enterGHpause↑ shiftend

Given model represents the electricity amount at x year.

Answered: Round answers to two decimal places. 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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(d) If the life expectancy is increased by 3.5 years in a certain country, how much will the happiness index change? Round to two decimal places. (e) Use the regression line to predict the happiness index of a country with a life expectancy of 84 years. Round to two decimal places.
Annabelle records the length, in inches, of a colored pencil over time. Review the table showing her data. Time (Weeks) Length (Inches) 0 7.5 2 7.5 4 7 5 6 7 2 8 1 10 0.5 12 0.25 13 0.2 Which description best fits the regression model for the data? logistic equation of the form y = , witha = 7.576, b = 0.001, and c = –1.107 logistic equation of the form y = , witha = 0.001, b = –1.107, and c = 7.576 trigonometric equation of the form y = a sin(bx + c) + d, with a = 4.15, b = 0.34, c = 497.43, and d = 3.80 trigonometric equation of the form y = a sin(bx + c) + d, with a = –4.15, b = –0.34, c = –497.43, and d = 3.80
The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the conference (Conf), average number of passing yards per attempt (Yds/Att), the number of interceptions throw attempt (Int/Att), and the percentage of games won (Win%) for a random sample of 16 NFL teams for one full season. Team Conf Yds/Att Int/Att win% Arizona Cardinals NFC 6.5 0.042 50.0 Atlanta Falcons NFC 7.1 0.022 62.5 Carolina Panthers NFC 7.4 0.033 37.5 Cincinnati Bengals AFC 6.2 0.026 56.3 Detroit Lions NFC 7.2 0.024 62.5 Green Bay Packers NFC 8.9 0.014 93.8 Houstan Texans AFC 7.5 0.019 62.5 Indianapolis Colts AFC 5.6 0.026 12.5 Jacksonville Jaguars AFC 4.6 0.032 31.3 Minnesota Vikings NFC 5.8 0.033 18.8 New England Patriots AFC 8.3 0.020 81.3 New Orleans Saints NFC 8.1 0.021 81.3 Oakland Raiders AFC 7.6 0.044 50.0 San Francisco 49ers NFC 6.5 0.011 81.3 Tennessee Titans…
The table shows the yield (in bushels per acre) and the total production (in millions of bushels) for com in a country for selected years since 1950. Let x represent years since 1900. Find a logarithmic regression model (y= a + b In x) for the yield. Estimate the yield in 2020. The regression model is y=+nx. (Round to one decimal place as needed.) The estimated yield in 2020 is bushels/acre. (Round to the nearest integer) Year 1950 1940 1970 1980 1990 2000 2010 *8828889 50 60 70 90 100 110 Yield 37 51 82 98 117 134 153
We would like to estimate a relationship between the weight of a car (weight) and the miles-per-gallon rating (mpg). lmpg - the natural logarithm of mpg lweight - the natural logarithm of weight Three models are estimated. Based on the regression outputs, do you prefer MODEL 1 or MODEL 2? 1.Linear model is preferred because its R-Squared is higher compared to log-linear model. 2.Not enough information to answer the question. 3.Log-linear model is preferred because its R-Squared is higher compared to linear model. 4.Log-linear model is preferred as SER is lower compared to linear model.
The local coffee shop keeps track of how much coffee they sell versus the temperature on that day, here are their figures: Sales in Php 1651 1757 1437 1525 1349 1231 Temp in Celsius 21.6 22.6 25 27.3 29.8 30.1 Suppose you want to create a regression equation that will predict the total sales in Php using the temperature of the day in Celcius, what is the total sales for the day in Php if the temperature is 31.5? Round your answers to the nearest hundredths.
What if the model is a conditional logistic model? Will the answer be anything different? Thank you.
Stores commonly offer a cheaper unit price for large quantity purchases. Quantity Unit Price 100.00 80.00 70.00 50.00 40.00 1 2 5 10 20 a. Use regression to find a logarithmic equation to model the data. Round the numbers in your equation to 2 decimal places. y = a + bln(x) with a= b = b. Use your equation to find an appropriate quantity for a customer who wishes to get a $35 unit price, accurate to the nearest whole number. c. Use your equation to find an appropriate quantity for a customer who wishes to get a $60 unit price, accurate to the nearest whole number.
For this exercise, round all regression parameters to three decimal places.The following table shows national health care costs, measured in billions of dollars. Date 1970 1980 1990 2000 2010 Costs inbillions 75 253 714 1353 2570 (a) Plot the data. (Let t be years since 1970 and H the costs in billions of dollars.) (b) Find an exponential function that approximates the data for health care costs. (Let t be years since 1970 and H the costs in billions of dollars.) _______ (c) By what percent per year were national health care costs increasing during the period from 1970 through 2010? (Use the model found in part (b). Round your answer to one decimal place.) ________% (d) Use functional notation to express how much money was spent on health care in the year 2012. (Let t be years since 1970.) H(_______) Estimate that value. (Use the model found in part (b). Round your answer to the nearest integer.)________ billion dollars
The table shows the yield (in bushels per acre) and the total production (in millions of bushels) for corn in a country for selected years since 1950. Let x represent years since 1900. Find a logarithmic regression model (y = a +b ln x) for the yield. Estimate the yield in 2023. Year 1950 1960 Yield 50 37 60 1970 1980 60 84 93 70 80 1990 90 116 2000 2010 100 136 110 157 The regression model is y =+( In x. (Round to one decimal place as needed.) bushels/acre. The estimated yield in 2023 is (Round to the nearest integer.)
Not long ago, Car and Driver magazine ran several sports cars as fast as they could down a 1-mile runway. The data they collected on one of the cars (a Lola Champ Car) is shown below.y=y= time (sec) speed (mph) 3.1 60 5.6 100 8.6 150 9.9 161.4 15 188.3 19.7 196.2 22 200 24.2 203.3 Use logarithmic regression to find a logarithmic function that best fits this data. y= Use logistic regression to find an logistic function that best fits this data.y=
1 YouTube .l 8:31 PM 10% 1 A cup of soup is left on a countertop to cool. The table below gives the temperatures, in degrees Fahrenheit, of the soup recorded over a 10-minute period. Time in Minutes (x) Temperature in °F (9) 180.2 165.8 146.3 135.4 127.7 110.5 4 8. 10 Write an exponential regression equation for the data, rounding all values to the nearest thousandth.

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