Answered: Which algorithm uses parametric line…

Which algorithm uses parametric line equations for clipping? - A) Cohen-Sutherland - B) Liang-Barsky - C) Sutherland-Hodgman - D) Midpoint subdivision.

Understanding Business

12th Edition

ISBN:9781259929434

Author:William Nickels

Publisher:William Nickels

Chapter1: Taking Risks And Making Profits Within The Dynamic Business Environment

Section: Chapter Questions

Problem 1CE

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d. Now based on regression analysis predict the number of patients that Dr. Fok will see in year 11 and 12 based on the forecasted Robbery Rate - year 11 is 117.1 and year 12 is 120.8. e. What is the MAD? f. What is the correlation Coefficient – r-value? % g. Based on the overall analysis, how well does each model fit the data?
Using multiple regression, you have identified P12,000 of unit level costs for 3,000 units, P1,000 of product level costs for 40 products, and P3,500 of customer-level costs for ten customers. The cost of Job 002 which used 800 unit level activities, 4 product level activities, and one customer-level activities amounts to * A. P3,650 B. P3,250 C. P3,050 D. P2,950
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Make an np chart for the following data: n non-conforming 400 12 400 10 400 8 400 14 400 21 400 16 400 18 400 15 400 12 400 17
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Dic 2 - Time Series Analysis and F eBook Problem 6-01 (Algorithmic) Consider the following time series data. Thm Week 1 2 3 4 5 6 Value 20 13 15 11 19 13 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. a. Mean absolute error. If required, round your answer to one decimal place. b. Mean squared error. If required, round your answer to one decimal place. c. Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places. % d. What is the forecast for week 7? If required, round your answer to two decimal place.
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Mop and Broom Manufacturing has tracked the number of units sold of their most popular mop over the past 24 months. This is shown. Month 1 2 3 4 5 6 7 8 Sales Month 238 249 254 267 277 282 402 296 9 10 11 12 13 14 15 16 Sales 300 327 346 349 353 364 373 363 Month + 17 18 19 20 21 22 23 24 Sales 361 381 375 383 384 401 409 403 a. Develop a linear trend line for the data. (Round your answers to 2 decimal places, e.g.,25.28.) Sales = (month) b. Compute a correlation coefficient for the data and evaluate the strength of the linear relationship. (Round your answer to 2 decimal places, the tolerance is +/-0.01.) Correlation coefficient is . It indicates linear relationship. (Use not rounded amounts to answer this question.) c. Using the linear trend line equation, develop a forecast for the next period,month 25. (Round your answer to 2 decimal places, the tolerance is +/-0.01. Do not round intermediate results used to achieve this answer.) Forecast for month 25 =
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answer a,b,c