Practice Time Series Visualization (3.4) - Advanced Data Visualization Techniques

Practice: Time Series Visualization

Lesson 3.4Advanced Data Visualization Techniques

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10 questions

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3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is a rolling window in time series analysis?
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Think about how we can smooth out data fluctuations.
Question 2.
List the three components of seasonal decomposition.
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Remember the acronym T-S-R!
3Question 3.
What is the purpose of using rolling windows in time series?
- To visualize all data points
- To smooth out short-term fluctuations
- To ignore long-term trends
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Think about why we might want to smooth data.
4Question 4.
Seasonal decomposition separates time series into which of the following components?
- Trend and seasonality
- Inputs and outputs
- Data and noise
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Remember the key acronym for seasonal decomposition.
Question 5.
Given a dataset with daily temperatures over a year, apply seasonal decomposition. Discuss how the trends vary and identify the major seasonal effects.
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Focus on each component's contribution and how they manifest in the time series.
Question 6.
Create an interactive time series plot that shows the financial performance of a company over five years, including seasonal effects and general trends.
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Incorporate dynamic elements that highlight seasonal trends.

6 more questions in this section. Enroll free to practise them all.