## What does time series data show?

A time series is a data set that tracks a sample over time. In particular, a time series allows one to see what factors influence certain variables from period to period. Time series analysis can be useful to see how a given asset, security, or economic variable changes over time.

## What are the characteristics of time series data?

When plotted, many time series exhibit one or more of the following features:

- Trends.
- Seasonal and nonseasonal cycles.
- Pulses and steps.
- Outliers.

**Which of the following is not present in a time series?**

variance is NOT a time series component, it refers to the spread of a data set.

**What are the components of time series data?**

An observed time series can be decomposed into three components: the trend (long term direction), the seasonal (systematic, calendar related movements) and the irregular (unsystematic, short term fluctuations).

### Which of the following are examples of time series data?

Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average.

### What are uses of time series?

Time series analysis is used to identify the fluctuation in economics and business. It helps in the evaluation of current achievements. Time series is used in pattern recognition, signal processing, weather forecasting and earthquake prediction.

**What are the main characteristics of time?**

The following are the basic characteristics of time.

- Involuntary. Time is often described as a 4th dimension with the others being length, width and height.
- Irreversible.
- Required.
- Measurable.
- Absolute Time.
- Time Dilation.
- Subjective Time.
- Arrow of Time.

**What are the four 4 main components of a time series?**

These four components are:

- Secular trend, which describe the movement along the term;
- Seasonal variations, which represent seasonal changes;
- Cyclical fluctuations, which correspond to periodical but not seasonal variations;
- Irregular variations, which are other nonrandom sources of variations of series.

## Which components of a time series is unpredictable?

Seasonality occurs when the time series exhibits regular fluctuations during the same month (or months) every year, or during the same quarter every year. For instance, retail sales peak during the month of December. This component is unpredictable.

## What are the types of time series?

Time series is a sequence of time-based data points collected at specific intervals of a given phenomenon that undergoes changes over time. It is indexed according to time. The four variations to time series are (1) Seasonal variations (2) Trend variations (3) Cyclical variations, and (4) Random variations.