Time Series Analysis in R
Skills you’ll Learn
About this Free Certificate Course
Time Series Analysis is a specific method of examining a sequence of collected data points over an interval of time. Time Series in R is used to observe how an object behaves over a certain period of time. Analysts record this data at consistent intervals to get accurate data points for the analysis. Time Series forecasting helps in predicting future values based on previously observed values.
This free course starts by explaining the base of Time Series forecasting. You will the various approaches utilized for Time Series forecasting. You will then get introduced to the Decomposition method and how it is used. You will learn about the irregularity concept in the decomposition method. To enhance your learning and understanding of the decomposition method, you will go through a case study on the decomposition method. You will then briefly understand the model forecast theory. Apart from all these theory concepts, you will also get the opportunity to enhance your experience in these concepts through hands-on sessions. You will go through a model forecast hands-on session in R and understand how it works. Next, you will have a hands-on exercise on Time Series forecasting in R. You will also get exposure to exponential smoothing function in R through a hands-on exercise on it. Enroll in this intermediate-level free Time Series Analysis in R course and understand all its concepts with a better approach. Earn a free certification in Time Series Analysis in R on completing the course.
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Frequently Asked Questions
What is Time Series Analysis in R?
Time Series Analysis in R analyzes how an object behaves over specific time intervals. R programming language has the relevant library support for this function to be attained. Hence, you can use the R language to get the results of the Time Series Analysis of an object.
How do you do a Time Series Analysis in R?
The R programming language supports Time Series Analysis through its ts() function with some parameters. This function takes some data vectors, and each of these data is related to the timestamp value provided by the user. This function is helpful in learning and forecasting the behavior of a business asset for a certain period of time.
What is Time Series forecasting in R?
Time Series Forecasting is a method of analyzing the Time Series data collected or recorded over a certain period of time. This helps make future predictions and forecast the values. The observations must be done regularly, and data must be collected at continuous intervals to attain Time Series Forecasting. Time Series Analysis in R is more accessible as it supports these methods through specific supportive functions.
How do you do Time Series Analysis step by step?
The step by step approach towards Time Series Analysis is as follows:
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Identify the Time Series data.
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Understand the stationary Time Series.
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Explore and understand the patterns in the Time Series Data.
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Decomposition of data.
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Smoothing the Time Series data.
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Estimate the Smoothing coefficient.
Will I get a certificate after completing this Time Series Analysis in R free course?
Yes, you will get a certificate of completion for Time Series Analysis in R after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.