Question: Hello, may you please answer the question and I will rate a thumbs? 11) An oscillating movement in demand that occurs periodically in the short

Hello, may you please answer the question and IHello, may you please answer the question and I will rate a thumbs?

11) An oscillating movement in demand that occurs periodically in the short run, and is repetitive is known as: A) Cycle B) Repetition C) Trend D) Period E) Beta 12) A seasonal factor is used to: A) Adjust the demand level corresponding to a specific period of time when there is seasonal oscillation B) Adjust the exponential smoothing when there is seasonal trend C) Adjust the demand for of linear regression when there is seasonal trend D) Adjust the demand for any forecasting method when there is a seasonal trend E) To find the preferred value of Beta when there is a seasonal trend 13) Which of the following statements is true? A) Any forecast method that is able to use more data points should be preferred B) Any forecast method that is more complex provides more accurate answers C) Nave forecast provides bad approximations when compared to other methods D) The parameter alpha and beta in adjusted exponential smoothing can be optimized to minimize error E) Simple moving averages with low number of periods provide a more stable result 14) In linear regression, the variable 'b' represents A) The intercept of a line that is representative of the data points available B) The slope of a line that is representative of the data points available C) The average value of the data points available D) The weight of the last data point as it is calculated by the method itself E) The value of the alpha as it is calculated by the method itself 15) In adjusted exponential smoothing, the variable 'beta' represents A) The weight of importance of the last data point B) The weight of importance of the historical data that is not the last data point C) The weight of importance of the slope between the last 2 data points D) The weight of importance of the slope between all data points E) The weight of importance between the most recent forecast and the previous forecast

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