The numbers of polio cases in the world are shown in thetable for various years.Year198819921996200020052007Number of Polio Cases (thousands)3501383043.21.3Let f(t) be the number of polio cases in thousands t yearssince 1980.Use a graphing calculator to draw a scattergram of thedata. Is it better to model the data by using a linear orexponential model? (ExponentialFind an equation of f. Hintf(t)coefficients to 4 decimal places.The number of polio cases is (decreasingper year.25.77%Predict the number of polio cases in 2013.HintRound thebyPredict in which year there will be 1 case of polio. HintyearsFind the approximate half-life of the number of poliocases. Hint

Year Number of Polio Cases 1988 350 1992 138 1996 30 2000 4 2005 3.2 2007 1.3 Let ft…

Answered: table for various years. Year 1988 1992…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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11. The table shows the temperature of coffee (in Fahrenheit) as a function of the number of minutes since the coffee was poured from the pot into a cup. a. Graph the data on your calculator. Why is an exponential function a better fit for the data than a linear function? Temp (*F) 179.5 Time (mins) 5 168.7 8 158.1 11 149.2 15 141.7 18 134.6 22 125.4 123.5 116.3 113.2 109.1 105.7 102.2 100.5 25 b. Find the exponential regression equation for the data Round decimals to 4 places. 30 34 38 42 45 50 c. Compare the y-intercept of the regression equation you found to the corresponding real data value. How close are these values? d. Use the regression equation to predict the temperature of the coffee after an hour. e. Graph the regression equation on your calculator. Create a window that has an XMAX of at least 420 (that's 7 hours!). TRACE on the graph to find the temperature of the function after 420 minutes. What is the temperature? Explain why using the function to model the temperature…
4 The data collected by a biologist showing the growth of a colony of bacteria at the end of cach hour are displayed in the table below. Time bour, Population () 250 330 580 800 1650 3000 3. Write an exponential regression equation to model these data. Round all values to the nearest thousandth. Assuming this trend continues, use this equation to estimate, to the nearest fen, the number of bacteria in the colony at the end of 7 hours.
page. 1. A bacteria colony initially has 4000 cells and triples every week. A function that can be used to model the population, p, of the colony after t days is a. p(t) = 4000(3)' с. %3D p(t) = 4000(3) 7 b. P(t) = 4000(2) d. p(t) = 4000(2) 7 %3D An investment of $100 is placed into an account that earns interest ompounded onnuolly € 50/ 6C.
enlearning.com/assessment/showtest php?begin ohm assessment-1 Rukayat Balogun User Settings My Classes Log o ger Forums Calendar Gradebook all 2018 > Assessment g Equations of Lines Due Fri 12/21/2018 10:00 am The population of a suburb of Phoenix has shown a linear growth in the years 1994-2006. The population in 1994 was 45980 people and it has been growing at a rate of 790 people per year A) Write a linear equation expressin Answer: g the population of the town, P, as a function of t, the number of years since 1994. Preview B) If the to wn is still expeencing a linear increase, what will the population be in 2008? Points possible: 1 Unlimited attenpts. Messags9 Submit 1:34 PM DRLL 2
ic SIS Days 1 2 Infected Individuals 678 722 a = 634.581 b = 1.073 2353 The table below shows the number of individuals infected with a disease t days after its first detected by the CDC. b = N X S For each of the following problems, enter regression equation values with at least 3 decimal places. Enter predictions to the nearest whole individual. ✓individuals III 3 4 5 756 825 882 1) Use regression to find an exponential equation that best fits the data above. The equation has form y = abt where: H 6 7 945 1017 individuals M Use the model to predict the number of individuals infected with the disease after 19 days. 8 1104 2) Use regression to find a linear equation that best fits the data above. The equation has form y = mt + b where: Use the model to predict the number of individuals infected with the disease after 19 days. 3) Use regression to find a quadratic equation that best fits the data above. The equation has form y = at² + bt + c where: S MyOpe
(O3) Helping tags: Statistics, Analysis of Relationships Among Variables, Logistic Regression Analysis, Linear Discriminant Analysis . . . . . . WILL UPVOTE, just pls help me answer the following questions in the attached image. Pls show complete solutions and explain them. Thank you!
Questions 6-9. Consider the data in the table. Absolute Relative Percent |Change Change Increase Time Value 13.60 17.00 2 21.25 3 26.56 |4 33.20 41.50 Which model would better represent this data, linear or exponential? Why? An exponential model would be better because the relative change is constant. A linear model would be better because the relative change is constant. A linear model would be better because the absolute change varies. An exponential model would be better because the absolute change is constant.
Suppose that the PDF for the number of years it takes to earn a Bachelor of Science (B.S.) degree is given as in the table below. P(x) 3 0.05 4 0.40 0.25 0.20 0.10 On average, how many years do you expect it to take for an individual to earn a B.S.? (Enter your answer to two decimal places.) 4.95 X years Additional Materials
Sunlight is absorbed in water, and as a result the light intensity in oceans, lakes, and ponds decreases exponentially with depth. The percentage of visible light -kx P (in decimal form) at a depth of x meters is given by P=e, where k is a constant related to the clarity and other physical properties of the water. The graph shows models for the open ocean, Lake Tahoe, and Lake Erie for data taken under similar conditions. Percent 0.8- 0.2- Percent of Surface Light vs. Depth -0.0491 x Ocean: P = e Tahoe: P = e -0.0799 x Depth (m) Erie: P = e -0.1980 x The euphotic depth for the open ocean is The euphotic depth is the depth at which light intensity falls to 1% of the value at the surface. This depth is of interest to scientists because no appreciable photosynthesis takes place. Find the euphotic depth for the open ocean. Round to the nearest tenth of a meter. meters. X

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