{"id":23131,"date":"2022-01-05T18:43:32","date_gmt":"2022-01-05T18:43:32","guid":{"rendered":"https:\/\/assignmenttutors.net\/blog\/enrollment-in-a-particular-class-for-the-last-four-semesters-has-been\/"},"modified":"2022-01-05T18:43:32","modified_gmt":"2022-01-05T18:43:32","slug":"enrollment-in-a-particular-class-for-the-last-four-semesters-has-been","status":"publish","type":"post","link":"https:\/\/assignmenttutors.net\/blog\/enrollment-in-a-particular-class-for-the-last-four-semesters-has-been\/","title":{"rendered":"Enrollment in a particular class for the last four semesters has been"},"content":{"rendered":"
\n

\u00a0<\/p>\n

1. Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130 (listed from oldest to most recent). Develop a forecast of enrollment next semester using exponential smoothing with an alpha = 0.2. Assume that an initial forecast for the first semester was 120 (so the forecast and the actual were the same). (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0118.96<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0121.17<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0130<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0120<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 2. 2. A seasonal index of ________ indicates that the season is average. (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a00.1<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a00.5<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a00<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a01<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 3. 3. Which of the following methods gives an indication of the percentage of forecast error? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0MAD<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0MSE<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0MAPE<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0decomposition<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 4. 4. Which of the following statements is not true about regression models? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0Estimates of the slope are found from sample data.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0The regression line minimizes the sum of the squared errors.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0The dependent variable is the explanatory variable.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0The intercept coefficient is not typically interpreted.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 5. 5. Which of the following is considered to be one of the components of a time series? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0trend<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0seasonality<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0cycles<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0All of the above<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 6. 6. A time-series forecasting model in which the forecast for the next period is the actual value for the current period is the (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0Delphi model.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0na\u00efve model.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0exponential smoothing model.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0weighted moving average.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 7. 7. Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day weighted moving average where the weights are 3 and 1 are (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a014.5.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a013.5.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a014.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a012.25.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 8. 8. Demand for soccer balls at a new sporting goods store is forecasted using the following regression equation: Y = 98 + 2.2X where X is the number of months that the store has been in existence. Let April be represented by X = 4. April is assumed to have a seasonality index of 1.15. What is the forecast for soccer ball demand for the month of April (rounded to the nearest integer)? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0123<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0107<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0100<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0115<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 9. 9. Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a three-day weighted moving average where the weights are 3, 1, and 1 (the highest weight is for the most recent number). (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a012.8<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a013.0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a070.0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a014.0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 10. 10. Which of the following statements is true regarding a scatter diagram? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It provides very little information about the relationship between the regression variables.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It is a plot of the independent and dependent variables.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It is a line chart of the independent and dependent variables.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It has a value between -1 and +1.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 11. 11. A judgmental forecasting technique that uses decision makers, staff personnel, and respondent to determine a forecast is called (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0exponential smoothing.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the Delphi method.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0jury of executive opinion.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0sales force composite.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 12. 12. When both trend and seasonal components are present in time series, which of the following is most appropriate? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the use of centered moving averages<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the use of moving averages<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the use of weighted moving averages<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the use of double smoothing<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 13. 13. When is the exponential smoothing model equivalent to the na\u00efve forecasting model? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0a = 0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0a = 0.5<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0a = 1<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0never<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 14. 14. Which of the following statements is true about r2? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It is also called the coefficient of correlation.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It is also called the coefficient of determination.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It represents the percent of variation in X that is explained by Y.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It represents the percent of variation in the error that is explained by Y.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 15. 15. If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0Y = a + bX is a good forecasting method.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0Y = a + bX is not a good forecasting method.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0a multiple linear regression model is a good forecasting method for the data.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0a multiple linear regression model is not a good forecasting method for the data.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 16. 16. Which of the following statements about scatter diagrams is true? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0Time is always plotted on the y-axis.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It can depict the relationship among three variables simultaneously.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0It is helpful when forecasting with qualitative data.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0The variable to be forecasted is placed on the y-axis.<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 17. 17. Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130. Suppose a one-semester moving average was used to forecast enrollment (this is sometimes referred to as a na\u00efve forecast). Thus, the forecast for the second semester would be 120, for the third semester it would be 126, and for the last semester it would be 110. What would the MSE be for this situation? (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0196.00<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0230.67<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0100.00<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a042.00<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 18. 18. Assume that you have tried three different forecasting models. For the first, the MAD = 2.5, for the second, the MSE = 10.5, and for the third, the MAPE = 2.7. We can then say: (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the third method is the best.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the second method is the best.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0methods one and three are preferable to method two.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0None of the above<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 19. 19. Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day moving average. (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a014<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a013<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a015<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a028<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

Question 20. 20. As one increases the number of periods used in the calculation of a moving average, (Points : 1)\u00a0<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0greater emphasis is placed on more recent data.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0less emphasis is placed on more recent data.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0the emphasis placed on more recent data remains the same.<\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0it requires a computer to automate the calculations.<\/p>\n

\u00a0<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

\u00a0 1. Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130 (listed from oldest to most recent). Develop a forecast of enrollment next semester using exponential smoothing with an alpha = 0.2. Assume that an initial forecast for the first semester was 120 (so the forecast and […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-23131","post","type-post","status-publish","format-standard","hentry","category-education"],"_links":{"self":[{"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/posts\/23131","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/comments?post=23131"}],"version-history":[{"count":0,"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/posts\/23131\/revisions"}],"wp:attachment":[{"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/media?parent=23131"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/categories?post=23131"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/assignmenttutors.net\/blog\/wp-json\/wp\/v2\/tags?post=23131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}