1. The population of Las Vegas, NV for the years 1980 – 2010 is given in the table below.t, the years since1020301980P(t), thepopulation164,674259,834484,487583,756Enter the above table in Desmos and use regression to find the best exponentialfunction of the form y = ab* to model the data (use the correct variables in yourwritten answer).а.b. Use your exponential model to predict the population of Las Vegas in 1990. How doesyour prediction compare with the actual population at that time?Use your exponential model to predict in what year the population of Las Vegas will beС.600,000.

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Answered: 1. The population of Las Vegas, NV for…

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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feyeb St Ral 5. Use regression to determine an exponential model for the following data. Round all parameters to 3 decimals. 15 20 22 10 d 140 250 410 780 1300 1670 CE OTTAS
5. Answer the problems completely. Round off your answers up to four decimal places, with correct units and box or encircle them.
Part D. Data from the Statistical Abstract of the United States provides a panel data collected at the state level in 1987 and 1990. These data are used to estimate MODEL 1: The variables used in the analysis are: infmort is number of deaths within the year per 1,000 live births Ipcinc is natural log of per capita income Ipopul is natural log of the population (the population is in thousands) Iphysic is natural log of physicians per 100,000 inhabitants d90 is year dummy for 1990. For questions 1 to 4 you can assume that MLR 1-4 are satisfied. A 1. Use the Stata output below to interpret ß3. Test at a 5% significance level whether the number of physicians per capita has any effect on infant mortality rate. reg infmort 1pcinc 1popul 1physic d90 Source Model Residual Total infmort infmort = Po + B₁lpcinc + B₂lpopul + ß3lphysic + 8₁ d90 + u SS 78.0499129 350.452136 428.502049 df . 19.5124782 4 97 3.61290862 Coef. Std. Err. MS 101 4.24259454 1pcinc -4.693354 1.638132 1popul - .0551426…
A 18.2% B 15.7% C 22.2% D 4.4%
62.6 08 4. Show graphically the regression equations of illustration 3.
Question 8 please
3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…
The following data gives the approximate population of the world for selected years from 1850 until2000. Year 1850 1900 1950 1980 2000 Population 1.3 (billions) 1.6 3 4.4 Assume that the population growth can be modeled with an exponential function p = bemx where x is the year and p is the population in billions. Use linearleast-squares regression to determine the constants b and m for which the function best fits the data. Use the equation to estimate the population in the year 1970.
7. Answer the problems completely. Round off your answers up to four decimal places, with correct units and box or encircle them.
The data presented is a multiple logistic regression analysis and the models are shown below. In the models below, the data are coded as follows: p = the proportion of children with a diagnosis of ADHD, Child Exposed and Father’s Diagnosis are coded as 1 = yes and 0 = no. What is the odds ratio adjusted for father’s diagnosis? (Hint: Use only the appropriate model to find the odds ratio) (1) = –2.216 + 1.480 Child exposed (2) Father with diagnosis: = –1.665 + 1.297 Child exposed (3) Father without diagnosis: = –2.343 + 0.823 Child exposed (4) = –2.398 + 1.501 Child exposed + 0.906 Father’s diagnosis
2. This question is about logistic regression. The outcome variable is success (1=success, 0=failure), and we have two groups of observations: group A and group B. a. Assume that on average, the odds of success is x for group A members. What is the average probability of success (p) for group A? Please write down p as a function of x. Given an x, is there a unique p? b. Assume that on average, the odds ratio for success of group A over group B is 2. The average probability of success for group A is pA and that the average probability of success for group B is pg. Is the set of Paand pg unique? c. The logistic regression of success ~ group (link=logit) returns a coefficient estimate of -1.3863 for the dummy variable group (1=group A, 0=group B). Interpret this coefficient estimate.
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