Government Analysis Function > Learning > Learning pathways > Time series learning pathway

Time series learning pathway

Description

Time series data, as opposed to cross-sectional data, is collected at discrete points in time to track changes in a real-world process over a given period. Time series data can be found in economics, social sciences, finance, epidemiology and the physical sciences. This pathway provides a basic conceptual understanding of time series data and time series analysis. It also focuses on applications of forecasting in time series analysis and deals with issues like seasonality and trends. This pathway prepares learners for more advanced practical courses in time-series analysis.

Learning objectives

  • Demonstrate an awareness in time series data and analysis with applications in various fields of study.
  • Understanding the importance of time series forecasting for predicting future events based on historical temporal data.
  • Know the components of time series data including seasonality, trends and noise.

Length

This pathway contains three courses.

Persona

To help decide if this is the pathway for you, this learning persona is designed to create a realistic representation of the intended learning audience.

General background

Suzy works in an Economic Statistics role.

Starting point

Suzy understands the concept of time series data but would like more exposure to forecasting and seasonal adjustment.

Perceived needs

Suzy has a basic understanding of economical and statistical concepts. However, in her role she will need to use forecasting techniques which is new to her.

Special considerations

Suzy prefers self-study to trainer-led courses. As she already has a basic understanding of the concepts she would like to progress through the learning at her own pace.

Summary

This pathway provides a basic conceptual understanding of time series data and time series analysis. It also focuses on applications of forecasting in time series analysis and deals with issues like seasonality and trends.

Enrol on this pathway

You can follow this learning pathway on the Learning Hub.

If you do not have a Learning Hub account, please contact Data.Science.Campus.Faculty@ons.gov.uk.

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