University of California, Los AngelesCOM SCI 6501XMidterm Quiz 2 _ ISYE6501x Courseware.VERIFIED CORRECT SOLUTIONS

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Midterm Quiz 2 - GT Students and Verified MM Learners Midterm Quiz 2 due Nov 8, 2020 23:00 PST Completed 90 Minute Time Limit Instructions Work alone. Do not collaborate with or copy from anyone e... lse. Work the problems in any order you wish, but submit each answer before ending the exam. You may use any of the following resources: One sheet (both sides) of handwritten (not photocopied or scanned) notes If any question seems ambiguous, use the most reasonable interpretation (i.e. don't be like Calvin): 11/22/2020 Good Luck! This is the beginning of Midterm Quiz 2. Please make sure that you submit all your answers before the time runs out. Once you submit an answer to a question, you cannot change it. There is no overall Submit button. After submitting all answers, please click the "End my Exam" button, above, before exiting from ProctorTrack to complete your exam. Information for Question 1 There are five questions labeled "Question 1." Answer all five questions. For each of the following five questions, select the probability distribution that could best be used to model the described scenario. Each distribution might be used, zero, one, or more than one time in the five questions. These scenarios are meant to be simple and straightforward; if you're an expert in the field the question asks about, please do not rely on your expertise to fill in all the extra complexity (you'll end up making the questions below more difficult than I intended). Question 1 0.0/1.4 points (graded) Time from the start of a World Cup soccer match until a goal is scored 11/22/2020 Answer: Weibull You have used 1 of 1 attempt Answers are displayed within the problem Question 1 1.4/1.4 points (graded) Number of phone calls made by a telemarketer until one is answered Answer: Geometric You have used 1 of 1 attempt Answers are displayed within the problem Question 1 1.4/1.4 points (graded) Time between people entering the ID-check queue at an airport Answer: Exponential You have used 1 of 1 attempt Answers are displayed within the problem Question 1 1.4/1.4 points (graded) Time between hits on a real estate web site Submit Submit Submit Exponential Geometric Poisson 11/22/2020 You have used 1 of 1 attempt Question 1 1.4/1.4 points (graded) Time from the beginning of Fall until the first snowflake is seen You have used 1 of 1 attempt Questions 2a, 2b 5.0/10.0 points (graded) Five classification models were built for predicting whether a neighborhood will soon see a large rise in home prices, based on public elementary school ratings and other factors. The training data set was missing the school rating variable for every new school (3% of the data points). Because ratings are unavailable for newly-opened schools, it is believed that locations that have recently experienced high population growth are more likely to have missing school rating data. Model 1 used imputation, filling in the missing data with the average school rating from the rest of the data. Model 2 used imputation, building a regression model to fill in the missing school rating data based on other variables. Model 3 used imputation, first building a classification model to estimate (based on other variables) whether a new school is likely to have been built as a result of recent population growth (or whether it has been built for another purpose, e.g. to replace a very old school), and then using that classification to select one of two regression models to fill in an estimate of the school rating; there are two different regression models (based on other variables), one for neighborhoods with new schools built due to population growth, and one for neighborhoods with new schools built for other reasons. Exponential Submit Submit Weibull 11/22/2020 Model 4 used a binary variable to identify locations with missing information. Model 5 used a categorical variable: first, a classification model was used to estimate whether a new school is likely to have been built as a result of recent population growth; and then each neighborhood was categorized as "data available", "missing, population growth", or "missing, other reason". a. If school ratings can be reasonably well-predicted from the other factors, and new schools built due to recent population growth cannot be reasonably well-classified using the other factors, which model would you recommend? Model 1 Model 2 Model 3 Model 4 Model 5 b. In which of the following situations would you recommend using Model 4? [All predictions and classifications below are using the other factors.] Ratings can be well-predicted, and reasons for building schools can be well-classified. Ratings can be well-predicted, and reasons for building schools cannot be wellclassified. Ratings cannot be well-predicted, and reasons for building schools can be wellclassified. Ratings cannot be well-predicted, and reasons for building schools cannot be wellclassified. 11/22/2020 You have used 1 of 1 attempt Answers are displayed within the problem Information for Question 3 In a diet problem (like we saw in the lessons and homework), let xi be the amount of food i in the solution (xi >= 0), and let M be the maximum amount that can be eaten of any food. Suppose we added new variables yi that are binary (i.e., they must be either 0 or 1): if food i is eaten in the solution, then it is part of the solution (yi = 1); otherwise yi = 0. There are five questions labeled "Question 3." Answer all five questions. For each of the following five questions, select the mathematical constraint that best corresponds to the English sentence. Each constraint might be used, zero, one, or more than one time in the five questions. Question 3 0.0/1.4 points (graded) Select the mathematical constraint that corresponds to the following English sentence: No amount of cheese sauce may be eaten unless the binary variable ycheesesauce is 1. ypeanutbutter + ycheesesauce = 0 ypeanutbutter = 1 − ycheesesauce ybroccoli ≤ ycheesesauce + ypeanutbutter ybroccoli + ycheesesauce + ypeanutbutter ≤ 2 [Show More]

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