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Explanation: The ARIMA model (AutoRegressive Integrated Moving Average) is one of the most robust techniques for forecasting time series data. It combines three components: autoregressive (AR), which uses past values to predict future ones; integrated (I), which accounts for differencing to stabilize the series; and moving average (MA), which models the error terms. ARIMA works well for non-seasonal data and requires pre-processing such as stationarity checks. It is widely used in finance, sales forecasting, and inventory management. Option A: Exponential smoothing techniques, not ARIMA, focus on smoothing data for short-term forecasting. Option B: ARIMA handles more than linear trends; it also accounts for autoregressive and moving average aspects. Option D: Decomposition is a preparatory step for analysis, not ARIMA’s primary role. Option E: Seasonal indices are relevant for seasonal models like SARIMA, not ARIMA.
If x 2 – 15x + 51 = 0, then determine the value of (x – 5) + {1/(x – 5)}.
√(92×8 ×52+700) = ?
{(21/20) + (20/21)}2 - {(21/20) - (20/21)}2 = ?
In a college, the proportion of boys to girls is 7:9, and the proportion of graduate students to postgraduate students is 4:5. Determine the total numbe...
The average of three numbers a, b and c is 2 more than c. The average of a and b is 48. If d is 10 less than c, then the average of c and d is:
If a3 + b3 = 6240 and a + b = 30, then find the value of {(a + b)2 – 3ab}
If 15a2 + 1 = 20a, then find the value of {(9a2 + 1)/25a2}
1/3 + 1/15 + 1/35 + 1/63 + 1/99 = ?
In a class of 70 students and 25 teachers, each student got gifts that were 20% of total number of students and each teacher got gifts that were 10% of ...