APPLIED STAT.IN BUS.+ECONOMICS
6th Edition
ISBN: 9781259957598
Author: DOANE
Publisher: RENT MCG
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Question
Chapter 12.11, Problem 45SE
a.
To determine
Find the predicted probability thata college graduate will lack insurance if the number of address changes is 0 using the fitted binary logistic regression.
b.
To determine
Find the predicted probability that a college graduate will lack insurance if the number of address changes is 3 using the fitted binary logistic regression.
c.
To determine
Find the predicted probability that a college graduate will lack insurance if the number of address changes is 6 using the fitted binary logistic regression.
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Check out a sample textbook solutionChapter 12 Solutions
APPLIED STAT.IN BUS.+ECONOMICS
Ch. 12.1 - For each sample, do a test for zero correlation....Ch. 12.1 - Instructions for Exercises 12.2 and 12.3: (a) Make...Ch. 12.1 - Prob. 3SECh. 12.1 - Prob. 4SECh. 12.1 - Instructions for exercises 12.412.6: (a) Make a...Ch. 12.1 - Prob. 6SECh. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - Prob. 9SECh. 12.2 - (a) Interpret the slope of the fitted regression...
Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.3 - Prob. 12SECh. 12.3 - Prob. 13SECh. 12.3 - The regression equation Credits = 15.4 .07 Work...Ch. 12.3 - Below are fitted regressions for Y = asking price...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - A regression was performed using data on 32 NFL...Ch. 12.5 - A regression was performed using data on 16...Ch. 12.6 - Below is a regression using X = home price (000),...Ch. 12.6 - Below is a regression using X = average price, Y =...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.7 - Refer to the Weekly Earnings data set below. (a)...Ch. 12.7 - Prob. 33SECh. 12.8 - Prob. 34SECh. 12.8 - Prob. 35SECh. 12.9 - Calculate the standardized residual ei and...Ch. 12.9 - Prob. 37SECh. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - Prob. 40SECh. 12.9 - Prob. 41SECh. 12.9 - Prob. 42SECh. 12.9 - Prob. 43SECh. 12.11 - Prob. 44SECh. 12.11 - Prob. 45SECh. 12 - (a) How does correlation analysis differ from...Ch. 12 - (a) What is a simple regression model? (b) State...Ch. 12 - (a) Explain how you fit a regression to an Excel...Ch. 12 - (a) Explain the logic of the ordinary least...Ch. 12 - (a) Why cant we use the sum of the residuals to...Ch. 12 - Prob. 6CRCh. 12 - Prob. 7CRCh. 12 - Prob. 8CRCh. 12 - Prob. 9CRCh. 12 - Prob. 10CRCh. 12 - Prob. 11CRCh. 12 - Prob. 12CRCh. 12 - (a) What is heteroscedasticity? Identify its two...Ch. 12 - (a) What is autocorrelation? Identify two main...Ch. 12 - Prob. 15CRCh. 12 - Prob. 16CRCh. 12 - (a) What is a log transform? (b) What are its...Ch. 12 - (a) When is logistic regression needed? (b) Why...Ch. 12 - Prob. 46CECh. 12 - Prob. 47CECh. 12 - Prob. 48CECh. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Prob. 50CECh. 12 - Prob. 51CECh. 12 - Prob. 52CECh. 12 - Prob. 53CECh. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Prob. 57CECh. 12 - Prob. 58CECh. 12 - Prob. 59CECh. 12 - Prob. 60CECh. 12 - Prob. 61CECh. 12 - Prob. 62CECh. 12 - Prob. 63CECh. 12 - Prob. 64CECh. 12 - Prob. 65CECh. 12 - In the following regression, X = weekly pay, Y =...Ch. 12 - Prob. 67CECh. 12 - In the following regression, X = total assets (...Ch. 12 - Prob. 69CECh. 12 - Below are percentages for annual sales growth and...Ch. 12 - Prob. 71CECh. 12 - Prob. 72CECh. 12 - Prob. 73CECh. 12 - Simple regression was employed to establish the...Ch. 12 - Prob. 75CECh. 12 - Prob. 76CECh. 12 - Prob. 77CECh. 12 - Below are revenue and profit (both in billions)...Ch. 12 - Below are fitted regressions based on used vehicle...Ch. 12 - Below are results of a regression of Y = average...Ch. 12 - Prob. 81CE
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- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardTable 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?arrow_forwardDoes a linear, exponential, or logarithmic model best fit the data in Table 2? Find the model.arrow_forward
- Sales of a video game released in the year 2000 took off at first, but then steadily slowed as time moved on. Table 4 shows the number of games sold, in thousands, from the years 20002010. a. Let x represent time in years starting with x=1 for the year 2000. Let y represent the number of games sold in thousands. Use logarithmic regression to fit a model to these data. b. If games continue to sell at this rate, how many games will sell in 2015? Round to the nearest thousand.arrow_forwardWhat is the y -intercept on the graph of the logistic model given in the previous exercise?arrow_forwardRespiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.arrow_forward
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