Consider the plot of the total number E of Ebola cases in West Africa reported to the Centers for Disease Control and Prevention from April 1, 2014, through December 1, 2015.D+|+|||||||||||||||| ►Ebola Cases in West AfricaE =A logistic fit for these data is given by27,841.421 + 134.65-0.646where t is the time in months since April 1, 2014. Below, we have added the graph of this model.+-+|||||||||||||||||| ►Logistic Graph Added(a) Does the first plot, "Ebola Cases in West Africa," show a continuing epidemic or a health crisis that is under control by December 2015?Because the data points appear to be [leveling off✔✔✔, they show a health crisis that is under control(b) According to the model, what was the total number of cases when the disease was spreading at the fastest rate? Round your answer to the nearest whole number.27021.61x cases(c) Use the crossing-graphs method to determine when the disease was growing at the fastest rate. Round your answer, in months after April 1, 2014, to one decimal place.24527x months

From the given information.Observe the given graphs.The logistic fit for the given data is as…

Answered: Consider the plot of the total number E…

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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Q8. Are rent rates influenced by the student population in a college town? Let rent be the average monthly rent paid on rental units in a college town in the United States. Let pop denote the total city population, avginc the average city income, and pctstu the student population as a percentage of the total population. One model to test for a relationship is log(rent) = 0.03048 + 0.5 * log(pop) +0.673 log(avginc) + 0.0046 pctstu (.844) (.039) (.081) (.0028) i) State the null hypothesis that the percentage of students relative to the population has no ceteris paribus effect on monthly rents. State the alternative that there is an effect. What signs do you expect for B₁ and ₂ ? The equation estimated for 64 college towns is log(rent) = 0.03048 + 0.5 * log(pop) + 0.673 log(avginc) + 0.0045 pctstu (.844) (.039) (.081) (.0017) Standard errors are given in the parentheses. test the null hypothesis H_0 that "10% ceteris paribus increase in population is associated with about a 6.6% increase…
Critically assess the goodness-of-fit measures of logit models.
Suppose a logistic model has been fitted to a data set and the ROC curve has been plotted. If the point with sensitivity = a and specificity = B is on the curve, what are the smallest and largest values for the area under the curve?
answer all the questions
A survey was conducted and asked: "Do you consider your health to be poor?" This was coded as 1 for "yes" and 0 for "no." The effect of age (in years) and sex (1 male, 0 = female) on the outcome was examined using logistic regression. The fitted logistic model is: = logit(ô) = −0.544 + ß * sex + 0.0331 * age (a) What are the odds of responding "yes" for a female subject who is 60 years old? (b) What is the estimated odds ratio corresponding to the age variable? Interpret this estimate. (c) Suppose that, based on the data from the survey, the odds of responding "yes" for males are 3.79% greater than the odds for females, adjusting for age. What is the value of Â? (d) If we only wanted to assess the association between survey response (yes/no) and sex, what other method(s) (that we have learned in this class) could we have used (name at least one)? In your own words, explain why we cannot use the same method(s) if we want to consider the effects of both sex and age on survey response.
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.
The following model studies the effect that a chemical spill disaster had on nearby housing values. They used data from a sample of houses sold in 1980, before chemical spill disaster happened, and a separate sample of houses sold in 1985, after chemical spill had occurred. where the variables used in the analysis are: log(price) is natural log of selling price in $ y85 is a dummy variable equal to 1 if a house was sold in 1985, 0 otherwise far is a dummy variable equal to 1 if a house was far from the affected area, 0 otherwise If the chemical spill reduces the value of houses closer to the affected area, which of the following statement is correct? Select one: O a. a₁ is expected to be positive O b. O c. O d. log(price) = a + Boy85 + a₁ far + B₁y85 * far + u a₁ is expected to be negative B₁ is expected to be positive B₁ is expected to be negative
True, or false? One reason it is usually wise to treat an ordinal variable with methods that use the ordering is that in tests about effects, chi-squared statistics have smaller df values and tend to be more powerful. The cumulative logit model assumes that Y is ordinal; it should not be used with nominal Y. The baseline-category logit model treats Y as nominal; it can be used with ordinal Y, but it then ignores the ordering.
Would you include ros in a final model explaining CEO compensation in terms of firm performance?
You are an econometrician working in the Ministry of Finance in Trinidad and Tobago and using a database consisting of 108 monthly observations on automobile accidents for Trinidad and Tobago between January 2011 and December 2019, you estimate the following model: log( totacc,) = B, + Bit + B2feb, + ßzmar.. + B12dec, + µe where totacc is the total number of accidents, t is time (measured in months), and feb,, mar,, dec, are dummy variables indicating whether time period t corresponds to the appropriate month. You obtain the following OLS results: Number of obs F( 12, Prob > F df 108 31.06 0.0000 0.7969 Source I MS 95) Model | 1.00244071 Residual | .255496765 12 .083536726 95 .00268944 R-squared Adj R-squared = 0.7712 Root MSE Total | 1.25793748 107 .011756425 - .05186 ltotacc | Coef. Std. Err. t P>It| [958 Conf. Interval] .0024274 -.0912208 .031287 .0027471 .0001611 .0244475 .0244491 17.06 0.000 .0030669 .0058479 .1283621 feb | -.0426865 mar | apr | may | jun | jul | aug | sep I oct I…

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