Q 1. The RMU community of 3,000 people is homogeneously mixed. Assume that one person (staff or student) returned to the community with COVID-19. There exists a mathematical model, which assumes that diseases tend to spread at a rate in direct. proportion to the mmber P who have the disease and to the mumber 3, 000- P who have not yet contracted the disease (logistic growth). The mathematical model i, 3000 P(t) 1+ 2999e 12 where P(t) is the number of people who have contracted the discase after t days. (a) How many people would have contracted the discase after 5, 10, 15, 20, 25 and 30 days? (b) How many days will it take until half of the community to have contracted COVID-19? th CamScanņer ) How many days will it take until the entire commmity contracts COVID-19?

Q 1. The RMU community of 3,000 people is homogeneously mixed. Assume that one person (staff or student) returned to the community with COVID-19. There exists a mathematical model, which assumes that diseases tend to spread at a rate in direct. proportion to the mmber P who have the disease and to the mumber 3, 000- P who have not yet contracted the disease (logistic growth). The mathematical model i, 3000 P(t) 1+ 2999e 12 where P(t) is the number of people who have contracted the discase after t days. (a) How many people would have contracted the discase after 5, 10, 15, 20, 25 and 30 days? (b) How many days will it take until half of the community to have contracted COVID-19? th CamScanņer ) How many days will it take until the entire commmity contracts COVID-19?

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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4. Consider the constant rate of decrease of certain microorganisms. At the start, there are 12,000 microorganisms in a certain place after 30 seconds, the population decreased to 8,000. If the number of microorganisms is directly proportional to the constant rate of decay and such a decrease in a number continues at the same rate, then how many microorganisms will there be after 45 seconds?
A nkcschools.instructure.com A population of 20 rabbits is introduced into an environment with a carrying capacity of 500 rabbits. The rabbit population increases by 10% every month. Make a logistic model that gives the number of rabbits N after t months. Use t as your variable and round r to three decimal places. Edit View Insert Format Tools Table 12pt v Paragraph v BIUA v ev T? v ...
Suppose that we want to build a model that predicts the group membership of a hurricane, either tropical (0) or non-tropical (1) based on the latitude of formation of the huricane. The response variable is the binary variable Type.new (type of hurricane) and the predictor variable is FirstLat (First Latitude). Using R, we build a model by applying the glm () function. For the logistic regression model, we specify family = "binomial". The data is available at https://userpage.fu-berlin.de/soga/200/2010 data sets hurricanes.xlsx. The R code is #set up filename my.filename 1z|) <2e-16 *** 0.96148 -9.446 0.37283 0.03947 9.447 <2e-16 *** --- *# Signif. codes: 0 '*** 0.001 **' 0.01 '*' 0.05'.' 0.1 '' 1 # (Dispersion parameter for binomial family taken to be 1) Null deviance: 463.11 on 336 degrees of freedom *# Residual deviance: 232.03 on 335 degrees of freedom *# AIC: 236.03 *# Number of Fisher Scoring iterations: 6 What is the interpretation of the p-value of the predictor variable…
Table 4.18 shows estimated effects for a fitted logistic regression model with squamous cell esophageal cancer (1 = yes, 0 = no) as the response variable Y. Smoking status (S) equals 1 for at least one pack per day and 0 other- wise, alcohol consumption (A) equals the average number of alcoholic drinks consumed per day, and race (R) equals 1 for blacks and 0 for whites. A. To describe the race-by-smoking interaction, construct the prediction equation when R = 1 and again when R = 0. Find the fitted YS conditional odds ratio for each case. Similarly, construct the prediction equation when S = 1 and again when S = 0. Find the fitted YR conditional odds ratio for each case. Note that, for each association, the coefficient of the cross-product term is the difference between the log odds ratios at the two fixed levels for the other variable. B. In Table 4.18, explain what the coefficients of R and S represent, for the coding as given above. What hypotheses do the P -values refer to for…
a) Logistically, the growth of Mrs. Fields cookies in different states is closely modeled after this: 19440 P(t) = 1 + 485 e -0.4444t P(t) is number of U.S. cities with a Mrs. Fields cookie storet years after the year 2000, and t is time in years after the year 2000. Use this logistic model to find the number of cities that had a Mrs. Fields cookie store in the year 2000, when they first opened. U.S. cities in the year 2000. b) How many U.S. cities had a Mrs. Fields cookie store in the year 2015. (round to the nearest whole number) U.S. cities in the year 2015.
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A quality control team studies the relationshipbetween years of experience (x) for individualdesign employees and ability to complete acomplex project within a certain time frame (y),where Y = 1 if the project is successfullycompleted, and Y = 0 if not. We know: b0 = −1.68and b1 = 0.12.a) Write the estimated logit function.b) Estimate the odds that a design employeewith 10 years of experience completes thecomplex project.c) Find and interpret the estimated odds ratiofor this model.
6. From 1790 to 1860, U.S. population grew rapidly (see the table). Let f(t) be the population t years after 1790. a) Create a scattergram for the data on your Graphing Calculator. b) Based on your scattergram, what appears more appropriate, a linear model, or an exponential model? Explain Year 1790 1800 1810 1820 1830 1840 1850 1860 d) What is the base? What does it tell us about the rate of population growth? Population (millions) 3.9 5.3 7.2 9.6 12.9 17.1 23.2 31.4 c) Use ExpReg on your GC to find an equation to model the situation. Write your answer using function notation. Round using 6 decimal places.
Consider the following estimated model, where the dependent variable is the log of the hourly wage: log(wage) = 0.417 - 0.238female + 0.17educ + 0.0232 exper - 0.00058exper? +0.0295tenure – 0.00059tenure? female 1 if the person is female, and 0 if the person is male educ = level of education, in years exper = level of expertise, in years tenure = duration of tenure, in years Given that the above regression model has 313 observations, then its degrees of freedom is equal to For the same levels of education, expertise, and tenure, women earn exactly % less compared to men, holding other factors fixed.