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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