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An Introduction to Time Series Analysis

Time Series is the collection of data points collected at regular or uniform intervals of time. Time series analysis of data happens in a wide range of fields like Finance, Economics, and Medicine. The examples of time series analysis in Economics include GDP data, monthly unemployment data, etc. In Finance, it includes stock prices, daily exchange rates and in environmental science, it includes temperature data, daily rainfall data, and others. For observing the pattern of time series data, one frequently used method is constructing a line chart against the given unit like day, week, or year. The Time Series Analysis assignment helpÂ of BookMyEssay consist of solutions to all the complex solutions that are related to the statistical problems. Our online tutors are efficient for teaching the students how to apply the concept and methods of time series methods on the online platform. Students can learn how to use a time series analysis for solving different managerial problems. Time series techniques apart from being used in Statistics and used widely in other fields of study like Signal Processing, Electrical Engineering, weather forecasting, pattern recognition, and earthquake prediction. Time Series Analysis case study writing help and homework help online on Time Series Analysis offered by BookMyEssay.

Time Series Analysis: An overview

Time Series Analysis is a technique used in Statistics that involves time data series. Time series data indicates the data is used in the series of intervals or time periods. This data is of three types:

• Time Series Data
• Cross-sectional Data
• Pooled Data

In time series, the points are indexed for monitoring the deviations and the changes that occur over a time period. The gaps between these periods are normally uniform. This is the reason it is also known as discrete data. Time series is plotted through line charts. These are hugely used for making predictions about an organization, econometrics, strategy making, weather forecasting, mathematical finance, astronomy, earthquake prediction, communications engineering, etc. It is an important tool for drawing conclusions and making conclusions used by the statisticians.

Time series is learned by using various methods. Some of them are the following:

• Linear method and non-linear method
• Parametric method and non-parametric method
• Univariate method and Multivariate method

Importance of Time Series Analysis

Time Analysis Analysis is mostly used by the strategic managers and statisticians. The advantages of using it are the following:

• It helps to determine the future course of economy or business
• It helps to find out the relation between any past and future activity
• It helps to develop a pattern that is used for the study.
• It is used as a control measure for meeting the requirements.

Some important aspects that should be considered at the time of preparing time series analysis are as follows:

• Before preparing time series analysis, there needs to be assurance that a pattern or a trend exists between past and future.
• Checking the sudden changes in data that affects the analysis
• Checking whether there is continuous change in data
• Ensuring seasonality in data

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Applications of Time Series Analysis

Time Series Analysis is an important tool and there are various applications of it in different industries.

• Forecasting – It is used in businesses for studying the changes and forecasting the future possibilities.
• Descriptive Analysis – It helps to determine the pattern or trend in a time series.
• Spectral Analysis – It identifies the cyclical changes that happen in the product sales.
• Intervention Analysis – It can determine whether an event can change a time series. It studies the sudden changes that make it fluctuate.

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