Time series l Statistics Paper 3 l Part 1 l ISS 2026

Welcome back to our channel! In this video we begin Part 1 of our deep-dive into the Time Series topic as per the Union Public Service Commission (UPSC) Indian Statistical Service (ISS) Statistics Paper 3 syllabus for the 2026 cycle.


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🎯 What you’ll get in this video

Introduction to Time Series Analysis: definition, components (trend, seasonal, cyclical, irregular)

How discrete-parameter stochastic processes relate to time series.

Methods of smoothing: moving averages, exponential smoothing.

Exploratory techniques: testing for trend & seasonality.

Setting up the groundwork for forecasting models (to be covered more in subsequent parts).



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📌 Why this is important for ISS Paper 3

The ISS syllabus lists Time Series Analysis under “Applied Statistics” topics: including components of economic time-series, trend, seasonal fluctuations, stationarity, AR, MA, ARMA, ARIMA models.

In Paper 3, questions often focus on both theory & methods (e.g., how to determine trend/seasonality, how to move from smoothing to model building).

Mastery of these basics will make the advanced material (Box–Jenkins ARIMA etc.) much easier to crack.



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🧠 How to use this video in your preparation

Pause & practice: Whenever I explain a method, take a moment to jot down the formula and work a simple numeric example.

Link to previous years’ papers: Past ISS Paper 3 questions often include parts on smoothing/trend & seasonal indices. Utilize the resources.

Revisit after Part 1: This video sets the foundation—after watching, revisit once we finish all parts to reinforce connections between methods.



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✅ Next Steps

Part 2 of “Time Series” will cover: stationary processes, properties of autocovariance & autocorrelation functions, model identification for AR, MA, ARMA.

Don’t forget to download the notes and PDF that accompany this session (link in the description/comment section).

Subscribe & hit the bell icon so you don’t miss Parts 2, 3, … of the series.



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📚 Recommended Reading / Resources

ISS Syllabus overview for Statistics Paper 3.

Previous years’ ISS Paper 3 practice questions (look up smoothing/trend/seasonality).

Online lectures and notes on time series smoothing and forecasting basics.