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Time series analysis excels in modeling data where observations are collected at regular intervals. Predicting stock prices is a classic example where past trends, seasonality, and volatility inform future price movements. Techniques like ARIMA or exponential smoothing can model these dynamics effectively. Time series forecasting aids traders and investors in making data-driven decisions. Why Other Options Are Wrong : A) Determining customer satisfaction scores : Survey responses are typically not time-dependent, making time series analysis irrelevant. C) Estimating employee turnover : This is better suited to logistic regression or predictive modeling. D) Identifying clusters : Clustering techniques like k-means focus on grouping, not time-based trends. E) Conducting hypothesis testing : This evaluates statistical significance rather than leveraging temporal data.
Which year did SEBI make BRSR mandatory for the top 1,000 listed entities by market capitalization?
Consider the following statements about Green Ammonia:
1. It is produced by using hydrogen from water electrolysis and nitrogen separated from ...
Process by which substances like carbon dioxide or oxygen can move across the cell membrane is called _________.
Consider the following statements regarding the Chhath Festival:
1. Patna district administration decided to deploy drones to manage Chhath Fes...
What new research facility has IIT Madras launched, recognized as the largest in Asia?
Which state’s Nagri Dubraj rice variety has got G.I tag?
Consider the following International Organizations:
1. SAARC
2. ASEAN
3. BIMSTEC
4. G 20
How ...
Who recently became the first woman officer in the Indian Air Force to be presented a gallantry award?
In which country was India's first overseas Jan Aushadhi Kendra inaugurated in July 2024?
Where was the world's largest carbon capture plant "Mammoth" recently inaugurated?