Unemployment numbers actually recorded in a town for the second quarter of the year 2000 were 4,700. The underlying trend at this point was 4,300 people and the seasonal factor is 0.92. Using the multiplicative model for seasonal adjustment, what is the seasonally-adjusted figure (in whole numbers) for the quarter?
Monthly sales have been found to follow a linear trend of y = 9.82 + 4.372x, where y is the number of items sold and x is the number of the month. Monthly deviations from the trend have been calculated and follow an additive model. In month 24, the seasonal variation is estimated to be plus 8.5.What is the forecast number of items to be sold in month 24? (to the nearest whole number)
Which of the following are necessary if forecasts obtained from a time series analysis are to be reliable? (i) There must be no unforeseen events (ii) The model used must fit the past data (iii) The trend must be increasing (iv) There must be no seasonal variation
What is the purpose of seasonally adjusting the values in a time series?
The following data represents a time series:
????? X?????? ?36????? Y??????? ?41????????? 34???????????? 38????? ?42
A series of three point moving averages produced from this data has given the first two values as 38 and 39. What are the values of (X, Y) in the original time series?
sing an additive time series model, the quarterly trend (Y) is given by Y = 65 + 7t, where t is the quarter (starting with t = 1 in the first quarter of 20X5). If the seasonal component in the fourth quarter is -30, what is the forecast for the actual value for the fourth quarter of 20X6, to the nearest whole number?
The trend for monthly sales ($Y) is related to the month (t) by the equation Y = 1,500 - 3t where t = 1 in the first month of 20X8. What are the forecast sales (to the nearest dollar) for the first month of 20X9 if the seasonal component for that month is 0.92 using a multiplicative model?
Which of the following are necessary if forecasts obtained from a time series analysis are to be reliable? (i) The trend must not be increasing or decreasing (ii) The trend must continue as in the past (iii) Extrapolation must not be used (iv) The same pattern of seasonal variation must continue as in the past
Under which of the following circumstances would a multiplicative model be preferred to an additive model in time series analysis?
A company's annual profits have a trend line given by Y = 20t - 10, where Y is the trend in $'000 and t is the year with t = 0 in 20X0.What are the forecast profits for the year 20X9 using an additive model if the cyclical component for that year is -30?