• Post category:StudyBullet-17
  • Reading time:5 mins read

Time Series Analysis with MS Excel - Attrition Patterns
Learn to analyse attrition patterns of a company using time series analysis with MS Excel

What you will learn

Get hands-on exposure to time series analysis using MS Excel

Implement applications of time series analysis in real life scenario

Learn basic excel formulas and visualization

Learn time series concept

Description

Time series data collected over different points in time breach the assumption of the conventional statistical model as correlation exists between the adjacent data points. This characteristic of the time series data breaches is one of the major assumptions that the adjacent data points are independent and identically distributed. This gives rise to the need of a systematic approach to study the time series data which can help us answer the statistical and mathematical questions that come into the picture due to the time correlation that exists.

Time series analysis holds a wide range of applications is it statistics, economics, geography, bioinformatics, neuroscience. The common link between all of them is to come up with a sophisticated technique that can be used to model data over a given period of time where the neighboring information is dependent.

In time series, Time is the independent variable and the goal is forecasting.


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Time series analysis is a statistical method to analyse the past data within a given duration of time to forecast the future. It comprises of ordered sequence of data at equally spaced interval. To understand the time series data & the analysis let us consider an example. Consider an example of Airline Passenger data. It has the count of passenger over a period of time.

Ample of time series data is being generated from a variety of fields. And hence the study time series analysis holds a lot of applications. Let us try to understand the importance of time series analysis in different areas.

  1. Field of Economics: Budget studies, census Analysis, etc.
  2. Field of Finance: Widely used in the field of finance such as to understand the stock market fluctuations, yield management, understand the market volatility, etc.
  3. Social ScientistΓ : Birth rates or death rates over a period of time and can come with the schemes in their interest.
  4. Healthcare: An epidemiologist might be interested in knowing the number of people infected over the past years. Like in the current situation the researchers might be interested in knowing the people affected by the coronavirus over a period of time. Blood pressure traced over a period of time can be used in evaluating a drug.
  5. Environmental Science: Environmental time series data can help us explain the rise in temperature over the past few years. Plot shows the temperature data over a period of time
English
language

Content

Introduction

Introduction to Project

Data and Formula

Employee Data
Formula Part 1
Formula Part 2
Formula Part 3

Attrition

Overall Attrition
Quarter Attrition
Quarter Attrition Trend Line Chart

Moving Average

Moving Average
Moving Average Continue

Seasonality

Seasonality Part 1
Seasonality Part 2
Seasonality Part 3

Forecasting and Model

Forecasting
Department
Level Model