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Explanation: Significant autocorrelation at lag kk k means that the value at a given time tt t is correlated with its value at time t−kt-k t − k . This predictable relationship is crucial in identifying patterns that can improve forecasting accuracy. High autocorrelation suggests that past values influence future values, forming the basis for autoregressive modeling. For instance, in stock market analysis, if prices at t−1t-1 t − 1 strongly correlate with tt t , autoregressive models like ARIMA are effective for prediction. Option A: Stationarity involves constant statistical properties over time, not autocorrelation. Option C: Seasonal decomposition deals with cyclical patterns, not autocorrelation. Option D: Random residuals indicate a well-fitted model, unrelated to autocorrelation. Option E: Significant autocorrelation indicates linear dependency, not independence.
A question is given followed by two arguments. Decide which of the arguments is/are strong with respect to the question
Question:
Find the missing term in the following series.
AD25, CE64, EF121, GG196, ______
Shamita's birthday was on 15 March 2020, which was a Sunday. If her husband's birthday was on 31 May 2020, on which day would it fall?
Select the number from among the given options that can replace the question mark (?) in the following series.
99, 123, 150, 180, 213, ?
Select the combination of letters that when sequentially placed in the blanks of the given series will complete the series.
Three of the following word pairs are alike in some manner and hence form a group. Which word pair does not belong to that group?
Select the pair that follows the same pattern as that followed by the two pairs given below. Both pairs follow the same pattern.
TIM : WKN
GUA : JWB
Which of the following options can replace the question mark (?) and complete the given number series?
8, 6, 32, 18, 128, ?