Step 1: Concept Understanding:
This question evaluates comprehension of time series analysis's purpose and applications. Time series analysis dissects sequential data points over time to detect patterns and generate forecasts.
Step 2: Detailed Analysis:
Each statement is examined:
(A) Time series analysis does not help to understand the behavior of a variable in the past.
This statement is false. A primary objective of time series analysis is to scrutinize historical data for patterns such as trends, seasonality, and cycles. Past understanding is vital for future prediction.
(B) Time series predict the future behavior of variable.
This statement is true. Forecasting is a principal application of time series analysis. Models are constructed by identifying historical data patterns to extrapolate and predict future values.
(C) Time series helps to plan future operations.
This statement is true. Businesses heavily depend on time series forecasts (e.g., sales, demand) for future planning, including inventory management, production scheduling, staffing, and budgeting.
(D) The main aim of the time series analysis is to derive conclusions after arranging the time series in a systematic manner.
This statement is true. Time series data is chronological. Systematic arrangement and analysis enable the derivation of conclusions regarding the underlying factors influencing a variable and its temporal behavior.
Step 3: Final Conclusion:
Statements (B), (C), and (D) accurately describe the purpose and utility of time series analysis. Statement (A) is inaccurate. Consequently, the correct option is (C).