4.) (For Marketing & Sales Analysts-Consultants). Four months after the deliveries ofgoods were affected by the granular lockdown due to the Covid-19 pandemic, amanufacturer noticed that sales had dropped from 100,000 units per month to 80,000units. If the sales follow an exponential pattern decline, what will they be afteranother 4 months? Note: Use the exponential model, y= Cekt, where t is measured inmonths.

Given the sales modely=Cektwhere y represents the sales per month in a given month tIt is also given…

Answered: (For Marketing & Sales…

Calculus: Early Transcendentals

8th Edition

ISBN:9781285741550

Author:James Stewart

Publisher:James Stewart

Chapter1: Functions And Models

Section: Chapter Questions

Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...

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Assume a simple logistic regression model for X and Y. We know: bo= -1.1 and b₁ = 0.4 Estimate P(Y= 1) when X = 1.
Average starting salaries for students using a placement service at a university have been steadily increasing. A study of the last four graduating classes indicates the following average salaries: $30,000, $32,000, $34,500, and $36,000 (last graduating class). Using a simple exponential smoothing model with α = 0.25, predict the starting salary for the next graduating class. Assume the initial forecast was $30,000 (the forecast and actual were the same).
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 (p) = = -0.544 + ß* sex + 0.0331 * age old? (a) What are the odds of responding "yes" for a female subject who is 60 years | (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?
A researcher is studying the effect of parents' level of education on educational achievement of individuals. Using data on completed years of education (educ), mother's level of education (motheduc), father's level of education (fatheduc), a measure of cognitive ability (abil), and logarithm of family income (l.income), the researcher estimates 4 models. Table (1) shows the OLS estimates for each model, with standard errors in parentheses underneath each coefficient. The dependent variable in all the models is educ. Model 1 Model 2 Model 3 Model 4 Independent variables L.income (0.2) 0.15 motheduc 0.27 0.18 0.17 (0.02) (0.03) 0.11 (0.02) 0.52 (0.03) 0.11 (0.02) 0.39 (0.03) 0.10 (0.02) 0.35 fatheduc abil 0.53 (0.03) 0.09 (0.01) 8.74 (0.03) (0.03) (0.03) 0.05 abil_squared ww (0.01) 8.74 6.94 (0.32) 1230 Intercept 8.4 (0.12) 1230 3899.97 0.38 Table (1) (0.31) 1230 (0.31) 1210 N SSR R-squared 3999.24 3785.24 3541.2 0.35 0.45 0.49 a. How the degrees of freedom in model (3) compare to the…
The total number of thousands of tons of coal produced per year over a 10-year period for a certain region is provided in the accompanying dataset. Use double exponential smoothing to determine which pairs of values for a and ß minimize MAD for this dataset. α = 0.1, p=0.9; a=0.5, ß= 0.2; x = 1, ß= 0.6 Click the icon to view the coal production data. First find the MAD for each pair of values, a and ß. (Type integers or decimals rounded to two decimal places as needed.) X В MAD 0.9 0.2 0.6 0.1 0.5 1 123 1 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 A Year 1 2 3 4 5 6 7 8 9 10 B Coal Production (thousands of tons) C 434333 434332.9 420420 420419.9 439047 439046.9 477192 477191.9 504182 504181.9 526959 526958.9 546824 546823.9 564878 564877.9 556704 556703.9 570973 570972.9 D
The Federal Bureau of Investigation (FBI), as part of its internal security mission, serves as a database for all the reported crimes committed in the United States. One question that might be of interest is does having more police officers reduce the number of homicides? To investigate this claim, the 2013 data from the twenty largest municipal cities was supplied by the FBI's Uniform Crime Report. Below are two observations from the dataset: > head (cities) City Pop Homicides Police Density MedHome Mayor 1 New York 8175.133 335 4.2595 27016.30 5.5390 1 2 Chicago 2695.598 414 4.4309 11843.58 1.8310 The variables included in the study are: Name of city Population of city in 1,000s of people Number of homicides in the year 2013 Number of police officers per 1,000 people Number of people per square mile Median home price in $100,000 1 if city has a "Strong Mayor" form of government; 0 if not City Рор Homicides Police Density MedHome Мayor Model: log(u;) = Bo + B1Police; + B2MedHome; +…
Consider the following estimated model, where the dependent variable is the log of the hourly wage: log(wage) = 0.417 +0.17educ +0.0295tenure - 0.00059tenure? educ = level of education, in years tenure = duration of tenure, in years What is turnaround value (or turning point) for tenure?
Fake a dataset using a logit model with 20 observations, 1 independent variable whose values are natural numbers between 1 and 5, (odds(x+1)/odds(x)) =1.139, and p=0.52. Show a screenshot of your dataset.
An investigator modeled the log-odds of getting stomach cancer as a function of number of servings of vegetables per week and the number of servings of red mean per week using logistic regression. The odds that a person gets stomach cancer if they have 4 servings of red meat a week are 1.2 times the odds of cancer for someone who has 3 servings of red meat a week. Suppose the fitted regression model is given as log-odds = -6 + 0.182 M – 0.105 V, where M = #servings of red meat per week and V = #servings of vegetables per week. What is the odds ratio representing the change in odds for an increase in one serving of vegetables? Give the answer to three decimal places.
A safety engineer uses simple logistic regression tostudy the relationship between occupancy years (x)and evacuation decision (y), under a majorhurricane forecast. Each occupant willevacuate (Y = 1) or stay (Y = 0). Sample dataprovides the estimated logit function:w = 2.83 − 0.24x. Estimate the odds that ahomeowner of 10 years will evacuate.
Please complete parts b and c

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