Consider the logit regression log(odds(QualExam)) = Bo + B1 * ParEduc + 62 * Awards. where QualExam is a binary variable that indicatespassing the exam if equal to 1, and failing the exam if 0, ParEduc indicates the parents' education level, and Awards is a binary variable that indicateshaving experience of obtaining award(s) if equal to 1, and not having experience if 0.Given the parents' average education level unchanged, the odds ratio is expected to beto those without awards. For an individual without awards and the parents' education level of 4, the estimated probability of passing the exam isapproximatelyfor an individual with awards to pass the exam comparingInterceptParEducAwards-10.532.980.48O A. 1.616; 80%.O B. 0.48; 4%.O C. 0.48; 80%.O D. 1.616; 4%.

Answered: Image /qna-images/answer/3d5f83bb-e5ce-44b4-9754-f4488f039541.jpg

Answered: for an individual with awards to pass…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
Consider the logit regression log(odds(QualExam)) = B, + B, * ParEduc + B2 + Awards, where QualExam is a binary variable that indicates passing the exam if equal to 1, and failing the exam if 0, ParEduc indicates the parents' education level, and Awards is a binary variable that indicates having experience of obtaining award(s) if equal to 1, and not having experience if 0. Given the parents' average education level unchanged, the odds ratio is expected to be for an individual with awards to pass the exam comparing to those without awards. For an individual without awards and the parents' education level of 4, the estimated probability of passing the exam is approximately_. Intercept ParEduc Awards -10.53 2.98 0.48 O A. 1.616; 4%. O B. 1.616; 80%. O C. 0.48; 4%. O D. 0.48; 80%.
Consider the logit regression log(odds(QualExam) = ßo + B, • ParEduc + B, • Awards. where QualExam is a binary variable that indicates passing the exam if equal to 1, and failing the exam if 0, ParEduc indicates the parents' education level, and Awards is a binary variable that indicates having experience of obtaining award(s) if equal to 1, and not having experience if 0. Given the parents' average education level unchanged, the odds ratio is expected to be _ for an individual with awards to pass the exam comparing to those without awards. For an individual without awards and the parents' education level of 4, the estimated probability of passing the exam is approximately_. ParEduc Awards Intercept -10.53 2.98 0.48 O A. 0.48; 80%. O B. 1.616; 80%. O C. 1.616; 4%. O D. 0.48; 4%.
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. What is the odds ratio for stomach cancer for someone who has 5 servings as opposed to someone who has 3 servings? Enter your answer to 3 digits beyond the decimal point.
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To monitor and improve its productivity, a company made an investigation and found out that the factor that affects the productivity the most is the absenteeism. The company data analytics department have collected data about the two variables (Productivity and Absenteeism) for the 12 past years as shown in the table below. Now the purpose of the company is to determine, through regression analysis, whether the productivity is statistically affected by the absenteeism level or not. Year Absenteeism Productivity (in number of absent worker) (in Million AED) 1 204 342 2 352 336 3 154 406 4 206 410 5 422 278 6 530 214 7 750 138 8 482 268 9 374 262 10 120 356 11 188 396 12 634 152 Questions: Construct a scatter diagram for the data about productivity and absenteeism then interpret the possible relationship that can be found. Construct a simple regression model to predict the…
You are a big soccer fan and you decide to gather information on the goal differential (goals scored - goals allowed) for your favorite team in the Premier League during the last season. You find that the average goal differential for home games (games that take place on the team's own stadium) was 1.37 and the average goal differential for away games (games that take place on the opponent team's stadium) was 0.32. With the data you have, if you regress goal differential (call it variable G) on a dummy variable (call it variable D) that takes the value 1 if the game is a home game and takes the value zero if the game is an away game, and obtain Ĝi = Bo + B₁ D₁, then, Bo will be equal to equal to and ₁ will be
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