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Exploratory Data AnalysishardMultiple ChoiceObjective-mapped

MLS-C01 Exploratory Data Analysis Practice Question

A data scientist is performing EDA on a time series dataset of daily sales. The data scientist observes a pattern that repeats every 7 days. Which characteristic of the time series is being observed?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Seasonality

A pattern that repeats at a fixed frequency (every 7 days) is called seasonality. Option A is wrong because trend is a long-term increase or decrease. Option C is wrong because autocorrelation measures correlation with lagged values, not a repeating pattern. Option D is wrong because stationarity refers to constant mean/variance over time.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Stationarity

    Why it's wrong here

    Stationarity is about constant statistical properties, not repeating patterns.

  • Autocorrelation

    Why it's wrong here

    Autocorrelation is a statistical measure, not the pattern itself.

  • Seasonality

    Why this is correct

    Seasonality is a periodic pattern with a fixed frequency.

  • Trend

    Why it's wrong here

    Trend is a long-term direction, not a repeating pattern.

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