Unit 2: Time Series

Week 1: (11 December to 17 December 2023)

Lecture 1. Introduction to Time Series

In this lecture, we will get aware about the concept of Time series and its utility.

Lecture 2. Components of Time Series I

In this lecture, two components namely, secular trend and seasonal variation were illustrated.

Lecture 3. Components of Time Series II

In this lecture, the remaining two components namely, cyclical variation and Irregular or random variation were illustrated.

Week 2: (18 December to 24 December 2023)

Lecture 1. Method of Semi-Averages

In this lecture, we will learn the method of semi-averages to identify the trend in the time series data.

Lecture 1A. Method of Progressive Averages

In this lecture, we will learn the method of moving averages to identify the trend in the time series data.

Lecture 2. Method of Moving Averages

In this lecture, we will learn the method of moving averages to identify the trend in the time series data.

Lecture 3. Examples on Method of Moving Averages

In this lecture, we will illustrate some examples of method of moving averages to identify the trend in the time series data.

Lecture 4. Method of Least squares

In this lecture, we will learn the method of least squares to identify the trend in the time series data.

Week 3: (25 December to 31 December 2023)

Lecture 1. Example on Method of Least Squares

In this lecture, we will illustrate an example on method of least squares to identify the trend in the time series data.

Lecture 2. Examples on Method of Least squares

In this lecture, we will illustrate some examples on method of least squares to identify the trend in the time series data..

Lecture 3. Simple average Method 

In this lecture, we will learn the simple average method to identify the seasonal variation in the time series data.

Lecture 4. Examples on Simple average Method 

In this lecture, we will illustrate some examples on the simple average method to identify the seasonal indices in the time series data.