Exercise 9-3 AlgoConsider a binary response variable y and two predictor variables x₁ and x2. The following table contains the parameter estimates ofthe linear probability model (LPM) and the logistic regression model, with the associated p-values shown in parentheses.VariableInterceptX1x2x₁ = 4; X₂ = 17x₁ = 4, X₂= 20LPM-0.30(0.02)0.39(0.03)-0.03(0.02)Logistic-1.80(0.06)0.97(0.07)a. What is the predicted probability implied by the linear probability model for x1 = 4 with x2 equal to 17-and 20?Note: Roundintermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and1 (not in %).x₁ = 4, X₂ = 17x₁ = 4, X₂= 20ŷ-0.20(0.06)b. What is the predicted probability implied by the logistic model for x₁ = 4 with x2 equal to 17 and 20?Note: Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probabilitybetween 0 and 1 (not in %).ŷ

The question is about regression.Given :To find :a ) Predicted probability implied by LPM for given…

Answered: Consider a binary response variable y…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

A catalog company builds a logistic regression (LR) model to predict the probability that a customer will buy from the catalog during a particular campaign (mailing). The LR model contains 2 independent variables: X1 spend per year in 1000's of dollars (so $2000 will be coded as X1 2) and X2= does customer possess a loyalty card (X2 1 means customer has loyalty card, X2 = 0 means customer does not have the card). Once the model is fitted, the LR coefficients are provided below: = Constant term (BETAO): - 3.5 (negative 3.5) X1 coeff. (BETA1): 0.6 X2 coeff.(BETA2): 1.5 What is the probability that a customer who spends $6000/year and who does NOT have a loyalty card will respond to the campaign? = O About 53% O About 15% About 33% O About 45%
A major brokerage company has an office in Miami, Florida. The manager of the office is evaluated based on the number of new clients generated each quarter. Data were collected that show the number of new customers added during each quarter between 2015 and 2018. A multiple regression model was developed with the number of new customers as the dependent and the following four independent variables: Period (1, …, 16): A variable that measures the trend; Q1 = 1 for first quarter, Q1 = 0 otherwise; Q2 = 1 for second quarter, Q2 = 0 otherwise; Q3 = 1 for third quarter, Q3 = 0 otherwise. Questions: 1. Explain each of the four slopes (Period, Q1, Q2, Q3). 2. How many new customers would you expect in the second quarter of the following year (2019)?
The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?
In a study in pre-term infants, a group where breast feeding is difficult because the mother gets home before the baby does, you run a logistic regression model where the independent variable is the mother's age and the dependent variable is whether the infant was breast feeding at discharge from the hospital. If the log odds for breast feeding for a 20 year old mom was -3.654 + (20) * 0.157 = -0.514, compute the predicted probability for breast feeding for a 20 year old mom. 0.598 / (1+0.598) O 0.598 0.598 / (1 - 0.598) -0.514 / (1+0.598)
Consider a binary response variable y and a predictor variable x. The following table contains the parameter estimates of the linear probability model (LPM) and the logistic regression model, with the associated p-values shown in parentheses. Variable Intercept x LPM Logistic -6.90 (0.06) 0.19 (0.06) a. Test for the significance of the intercept and the slope coefficients at the 5% level in both models. Coefficients Intercept Slope -0.67 (0.02) 0.07 (0.03) LPM Logistic b. What is the predicted probability implied by the linear probability model for x=20 and x= 35? Note: Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %).
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 563. The equation of the regression line is y = 31.554x + 18,074.624. 405 458 690 482 492 389 53 53 156 Proceeds, y 17,788 28,282 43,709 30,030 36,947 36,625 22,282 10,561 31,747 29,048 Issues, x 190 Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 563. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where. "3.12 million" means 3,120,000.) O A. We can be 95% confident that when there are 563 issues, the proceeds will be between $ OB. There is a 95% chance that the predicted proceeds given 563 issues is between $ and $ and $ Ir
The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. In a particular region, 26.5 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is $29,889. Is this income higher or lower than what you would expect? Why?
In a study investigating maternal risk factors for congenital syphilis, syphilis is treated as a binary outcome variable, where 1 represents the presence of disease in a newborn and 0 represents absence of disease. The estimated coefficients from a logistic regression model containing the predictors cocaine or crack use, marital status, number of prenatal visits to a doctor, alcohol use and level of education are included in the table below. The estimated intercept is not included in the table. a. As an expectant mother’s number of prenatal visits to the doctor increases, does the probability that her child will be born with congenital syphilis increase or decrease?b. Marital status is a binary variable, where 1 indicates that a woman is unmarried and 0 indicates that she is married. What are the estimated relative odds that a newborn will suffer from syphilis for unmarried versus married mothers after holding the other variables in the model constant?c. Cocaine or crack use is also a…
A professor has found that scores on the midterm exam in her classes predict scores on the final exam. The regression constant in the linear prediction rule for predicting final exam scores from midterm exam scores is 31 and the regression coefficient is 0.5. Complete parts (a) through (k) below. (a) Indicate the predictor variable.
The following table gives the sales of CD_Rom drives and compact disk players for selected years and can be found in Glassman. Sales are in millions. Year 1988 1990 1992 1993 Sales 0.075 0.24 1.5 4.8 A. On the basis of this data, find the best-fitting exponential regression. Let x = 0 correspond to 1988. State the square of the correlation coefficient. (Use 4 decimal places in you answers.) S(x) = r2 = B. Use this model the estimate the sales in 1997. (Round to the nearest player.) In 1997, there were about million CD_ROM and compact disk players sold.
A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x). The results of the regression were: ý=a+bx a=-1.692 b=0.117 (a) Write the equation of the Least Squares Regression line of the form (b) Which is a possible value for the correlation coefficient, r? O -0.649 O 1.32 O 0.649 O-1.32 (c) If a country increases its life expectancy, the happiness index will O increase O decrease (d) If the life expectancy is increased by 2.5 years in a certain country, how much will the happiness index change? Round to two decimal places. (e) Use the regression line to predict the happiness index of a country with a life expectancy of 75 years. Round to two decimal places.
Logistic and Cox proportional hazards regression are used widely in medical and epidemiologic studies for analyzing the relationship between several risk factors and a time-related dichotomous response variable. Suppose we are studying the risk factors associated with mortality of Covid-19 patients admitted to hospitals in the Philippines. The response variable is whether or not the patient with Covid-19 died at the end of their hospitalization. Other variables recorded were: the time to death of the patient, sex, age, vaccinated or not vaccinated, presence of comorbidities, severity of Covid-19, variant of Covid-19, etc. In this study, would you prefer using the logistic regression or the Cox PH regression? Justify your answer. Site some of the advantages and disadvantages of preferring one method over the other. NOTE: other answer aside from the previous one on the tutor here in bartleby. Don't copy paste it pls

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS