Sample Quizzes For Preparation: Time Series
O Level and IGCSE Statistics – Quiz: Time Series
Question 1
What is the main purpose of calculating a moving average in a time series?
A. To identify outliers in the data
B. To highlight seasonal fluctuations
C. To smooth short-term fluctuations and identify trends
D. To calculate mean variation
Question 2
Which of the following best describes a seasonal variation?
A. Irregular data changes
B. Long-term changes in a data series
C. Repeating changes at regular intervals due to time-based factors
D. Data errors or random fluctuations
Question 3
What is the result of (24 + 27 + 30) ÷ 3 when calculating a 3-point moving average?
A. 25
B. 27
C. 28
D. 29
Question 4
Which of the following is required for calculating a centered moving average?
A. An odd number of data points
B. Seasonal variation values
C. Even-numbered period moving averages
D. Trend line slope
Question 5
Which type of data pattern does a trend describe in a time series?
A. Short-term irregular changes
B. Medium-term variations
C. Long-term direction in the data
D. Seasonal peaks and troughs
Question 6
If the actual value is 150 and the trend value is 144, what is the seasonal variation?
A. -6
B. +6
C. -12
D. +12
Question 7
What is the forecasted value if the trend is 190 and the seasonal variation is -10?
A. 180
B. 190
C. 200
D. 210
Question 8
Which method is best to remove seasonal variation from time series data?
A. Mean
B. Mode
C. Moving average
D. Median
Question 9
Which of the following is a typical source of seasonal variation?
A. Business cycles
B. Festivals or holidays
C. Earthquakes
D. Technological changes
Question 10
Which of the following best describes a time series?
A. Random numbers recorded monthly
B. A set of values recorded at irregular intervals
C. Data collected over regular time intervals
D. Data that cannot be forecasted
Question 11
What is a key assumption when using time series forecasting?
A. Trends and seasonal patterns remain stable over time
B. Random variations dominate all data
C. Data points are unrelated
D. Future values are unpredictable
Question 12
What is the seasonal variation if the actual value is 200 and the moving average (trend) is 188?
A. +12
B. -12
C. +8
D. -8
Question 13
A centered moving average is used to:
A. Remove trend from the data
B. Smooth seasonality
C. Improve alignment of averages to actual time periods
D. Amplify fluctuations
Question 14
Which of the following tools is essential to graphically identify a trend in time series data?
A. Histogram
B. Line graph
C. Bar chart
D. Pie chart
Question 15
If you want to predict sales for next quarter, you need:
A. Mean of the previous year’s data only
B. Just the seasonal variation
C. Trend and seasonal variation
D. Mode of the previous quarters
Question 16
Why is seasonal variation subtracted from actual data when deseasonalising?
A. To remove outliers
B. To focus on long-term trend
C. To estimate random error
D. To increase the trend value
Question 17
Which of the following is not a component of time series?
A. Trend
B. Random variation
C. Cyclical variation
D. Horizontal variation
Question 18
Seasonal variations are usually calculated for how many time periods in a year (e.g., quarters)?
A. 2
B. 3
C. 4
D. 12
Question 19
Which method best forecasts next year’s Q3 sales?
A. Multiply the seasonal variation of Q1
B. Add the Q3 seasonal variation to trend forecast
C. Use previous year’s Q3 actual value
D. Take average of Q1, Q2, and Q4
Question 20
Which data point is ignored when calculating the first 3-point moving average in a time series?
A. First data point
B. Second data point
C. Third data point
D. Fourth data point
Question 21
What do we call the line that shows the general direction of data in a time series graph?
A. Line of best fit
B. Seasonal line
C. Trend line
D. Graphical axis
Question 22
In a line graph, consistent rise in values across months shows a:
A. Cyclical variation
B. Seasonal variation
C. Downward trend
D. Upward trend
Question 23
What is the purpose of deseasonalising data?
A. To adjust for inflation
B. To remove long-term trends
C. To eliminate seasonal effects
D. To calculate monthly averages
Question 24
Which of the following components is NOT needed to draw a forecast graph?
A. Trend
B. Random error
C. Seasonal component
D. Time axis
Question 25
Which best describes the pattern in this time series: 100, 110, 120, 130, 140?
A. No trend
B. Seasonal drop
C. Upward trend
D. Downward trend
Question 26
How do you calculate the seasonal component of Q1 if Q1 actual = 105 and trend = 100?
A. 105
B. +5
C. -5
D. 100
Question 27
If trend is 180, and Q4 seasonal component = +10, forecast = ?
A. 190
B. 170
C. 180
D. 200
Question 28
What kind of fluctuation is caused by random or unpredictable factors in a time series?
A. Seasonal
B. Cyclical
C. Random
D. Trend
Question 29
Which method is best for removing irregular changes from data?
A. Trend line
B. Histogram
C. Moving average
D. Frequency polygon
Question 30
If Q2 values are consistently 10 units above the trend over 5 years, the average seasonal variation for Q2 is:
A. 10
B. -10
C. 5
D. 0
Marking Key and Detailed Explanations – O Level and IGCSE Statistics Quiz (Time Series)
| Q | Answer | Explanation |
|---|---|---|
| 1 | C | A moving average helps to smooth out short-term fluctuations, allowing the long-term trend to become visible. |
| 2 | C | Seasonal variation refers to regular, predictable changes that occur every year due to seasonal factors (e.g. holidays, weather). |
| 3 | B | (24 + 27 + 30) ÷ 3 = 81 ÷ 3 = 27. |
| 4 | C | A centered moving average involves even-numbered period averages which are averaged again to align with the original time periods. |
| 5 | C | A trend shows the long-term general direction (upward, downward, or constant) in the data. |
| 6 | B | 150 – 144 = +6 seasonal variation. |
| 7 | A | 190 + (-10) = 180 forecasted value. |
| 8 | C | Moving averages eliminate seasonal and irregular effects to isolate the trend. |
| 9 | B | Seasonal variation is typically caused by regular factors like festivals, holidays, or weather changes. |
| 10 | C | Time series data must be collected at regular time intervals (e.g. monthly, quarterly). |
| 11 | A | Time series forecasting assumes that patterns (trend/seasonality) remain consistent into the future. |
| 12 | A | 200 – 188 = +12 seasonal variation. |
| 13 | C | Centering aligns moving averages to time periods to improve accuracy when plotting trends. |
| 14 | B | Line graphs help visualize trends over time. |
| 15 | C | Forecast = trend + seasonal variation. |
| 16 | B | Deseasonalising removes repeating seasonal components to study the underlying trend. |
| 17 | D | There is no such thing as “horizontal variation” in time series analysis. |
| 18 | C | Quarterly data has 4 seasons (Q1 to Q4), so 4 seasonal variations. |
| 19 | B | To forecast Q3, you need to add Q3 seasonal component to the trend. |
| 20 | A | The first data point can’t form a full 3-point moving average window. |
| 21 | C | A trend line shows the overall long-term movement in the data. |
| 22 | D | A consistent increase in values indicates an upward trend. |
| 23 | C | Deseasonalising removes seasonal fluctuations for clearer analysis. |
| 24 | B | Random errors are not plotted or used in predictions—trend and seasonality are. |
| 25 | C | The values are increasing by 10 units consistently — upward trend. |
| 26 | B | 105 – 100 = +5 seasonal component. |
| 27 | A | 180 (trend) + 10 (seasonal) = 190 forecast. |
| 28 | C | Random fluctuations are irregular, unpredictable elements in time series. |
| 29 | C | Moving averages remove random and seasonal noise to reveal trend. |
| 30 | A | Average of 10 units above trend for Q2 each year = +10 average seasonal variation. |