1. Question 1

What is a trend?

• ❌ A consistent downward direction

• ❌ A consistent flat direction

• ❌ A consistent upward direction

• ✅ An overall direction for data regardless of direction

Explanation:
A trend can be upward, downward, or flat—it simply means an overall direction.

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2. Question 2

In time series, what is noise?

• ❌ Data without trend

• ❌ Data without seasonality

• ❌ Sound waves

• ✅ Unpredictable changes in time series data

Explanation:
Noise = random, unpredictable fluctuations.

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3. Question 3

Example of a Univariate time series?

• ❌ Hour by hour weather (multivariate: temp, humidity, wind…)

• ❌ Fashion items

• ✅ Hour by hour temperature

• ❌ Baseball scores

Explanation:
Univariate = only one variable changing over time.

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4. Question 4

What is autocorrelation?

• ❌ Data with no noise

• ❌ Data with predictable trends

• ✅ Data that follows a predictable shape, even if the scale is different

• ❌ Data aligning seasonally

Explanation:
Autocorrelation = similarity between current values and past values of the same series.

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5. Question 5

Example of a Multivariate time series?

• ❌ Hour by hour temperature (one variable)

• ❌ Baseball scores

• ✅ Hour by hour weather

• ❌ Fashion items

Explanation:
Weather contains multiple variables → multivariate.

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6. Question 6

What is a non-stationary time series?

• ❌ Consistent across seasons

• ❌ A constructive event forming trend + seasonality

• ❌ A disruptive event breaking trend + seasonality

• ✅ One that moves seasonally

Explanation:
Non-stationary data changes its statistical properties (mean, variance) over time—often due to trends or seasonality.

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7. Question 7

What is imputed data?

• ❌ Data withheld

• ✅ A projection of unknown (past or missing) data

• ❌ A bad prediction

• ❌ A good prediction

Explanation:
Imputation fills in missing data, often based on interpolation or statistical estimation.

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8. Question 8

A sound wave is time series data.

• ❌ False

• ✅ True

Explanation:
A sound wave is intensity changing over time → classic time series.

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9. Question 9

What is Seasonality?

• ❌ Data only available certain times of year

• ❌ Data aligned to calendar seasons

• ✅ A regular change in shape of the data

• ❌ Weather data

Explanation:
Seasonality = recurring, predictable pattern at regular intervals (daily, weekly, yearly, etc.).

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🧾 Summary Table

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