1. Which of the following is NOT considered a component of time series variations?
A. Secular Trend
B. Seasonal Variation
C. Probability Distribution
D. Cyclical Variation
Time series has four major components: Secular Trend, Seasonal Variation, Cyclical Variation, and Irregular/Random Variation. Probability distribution is a separate statistical concept, not a time series component.
2. Seasonal variation in a time series usually repeats after a fixed period of:
A. One year
B. Five years
C. Ten years
D. One month
Seasonal variations occur regularly within a year (quarterly, monthly, weekly, or daily). For example, ice cream sales peak every summer.
3. Which method is most commonly used for studying secular trend in a time series?
A. Moving Average Method
B. Least Squares Method
C. Semi-Average Method
D. All of the above
All three methods—Moving Average, Least Squares, and Semi-Average—are used to estimate the long-term trend (secular trend) in a time series.
4. Cyclical variations in a time series are generally associated with:
A. Seasonal demand patterns
B. Business and economic cycles
C. Random shocks
D. Long-term technological progress
Cyclical variations reflect upswings and downswings in economic activity, typically over a period longer than one year (e.g., boom and recession cycles).
5. Irregular variations in time series are mainly caused by:
A. Population growth
B. Business cycles
C. Natural calamities, wars, and strikes
D. Seasonal changes
Irregular variations are unpredictable fluctuations caused by unexpected events such as earthquakes, floods, pandemics, or strikes.
6. The main objective of trend analysis in time series is to:
A. Study short-term fluctuations
B. Eliminate random variations
C. Measure seasonal influences
D. Study long-term movement of data
Trend analysis identifies the long-term direction or movement in a time series, separating it from seasonal, cyclical, and irregular variations.
7. Which of the following is NOT a method of measuring trend?
A. Free-hand curve method
B. Semi-average method
C. Index number method
D. Least squares method
Index number method is not used for trend analysis. The common trend estimation methods are: free-hand curve, semi-average, moving average, and least squares.
8. In the semi-average method of trend analysis, the data series is divided into:
A. Two equal parts
B. Three equal parts
C. Four equal parts
D. Five equal parts
In the semi-average method, the time series data is split into two equal parts, averages are calculated, and then a trend line is drawn through these points.
9. The moving average method is most suitable when the time series data shows:
A. Sudden irregular variations
B. Strong seasonal fluctuations
C. Random shocks
D. No trend at all
The moving average method smooths short-term fluctuations and highlights underlying seasonal or trend patterns, making it effective where seasonality is strong.
10. In the method of least squares, the trend line is fitted such that:
A. The line passes through the first and last data points
B. The slope of the line equals the average growth rate
C. The sum of squares of deviations between actual and estimated values is minimum
D. The line has zero intercept
The least squares method ensures the best fit by minimizing the sum of squared deviations of actual values from the estimated trend line.
11. Cyclical variations in time series generally have a periodicity of:
A. Less than 1 year
B. More than 1 year
C. Exactly 1 year
D. Less than 6 months
Cyclical variations represent long-term business or economic cycles such as boom, recession, depression, and recovery, and they typically last more than one year.
12. Which of the following is the most appropriate example of seasonal variation?
A. Higher demand for air conditioners during summer
B. Fluctuations in stock market prices
C. Long-term increase in agricultural production
D. Unemployment due to economic recession
Seasonal variations repeat at regular intervals within a year, e.g., AC sales rise every summer, ice-cream sales peak in hot months.
13. Which method is commonly used to measure seasonal variations in time series?
A. Semi-average method
B. Free-hand curve method
C. Ratio-to-moving-average method
D. Least squares method
The ratio-to-moving-average method is widely used to compute seasonal indices by eliminating trend and cyclical effects.
14. If the seasonal index for sales in December is 120, it means:
A. Sales are 120% lower than average
B. Sales are 20% below the trend value
C. Sales are exactly at average level
D. Sales are 20% higher than the average
A seasonal index of 120 indicates that sales in December are 20% higher than the average monthly sales.
15. Which of the following statements best differentiates cyclical and seasonal variations?
A. Cyclical variations last more than a year, seasonal variations repeat within a year
B. Both cyclical and seasonal variations repeat annually
C. Seasonal variations are unpredictable while cyclical are predictable
D. Both are irregular variations
Seasonal variations occur regularly within a year (e.g., festivals, weather), whereas cyclical variations extend beyond a year and are tied to economic/business cycles.
16. Irregular variations in a time series are also called:
A. Secular trends
B. Random variations
C. Cyclical variations
D. Seasonal variations
Irregular variations are also called random or residual variations because they arise unexpectedly and cannot be predicted using historical patterns.
17. Which of the following is the BEST example of irregular variation?
A. Increase in sales during Diwali
B. Expansion in economy leading to higher employment
C. Drop in production due to sudden flood
D. Long-term population growth trend
A sudden flood is an irregular factor since it is unexpected, uncontrollable, and not repetitive like seasonal or cyclical variations.
18. Which of the following statistical techniques is most suitable for measuring irregular variations?
A. Moving averages
B. Least squares trend line
C. Seasonal index method
D. No specific method, as they are unpredictable
Irregular variations cannot be measured using systematic statistical methods because they occur unexpectedly due to natural disasters, wars, pandemics, etc.
19. The impact of irregular variations on business forecasting is usually:
A. Short-term and unpredictable
B. Long-term and systematic
C. Seasonal and repetitive
D. Negligible in all cases
Irregular variations generally create short-term disruptions in business activities and are unpredictable, but their effect may sometimes be severe.
20. Which of the following correctly differentiates irregular variations from other components of time series?
A. They occur regularly every year
B. They follow a fixed cycle of 5–10 years
C. They are accidental, unexpected, and do not follow a pattern
D. They are long-term upward or downward movements
Irregular variations are accidental or unexpected factors (like strikes, wars, earthquakes) that do not repeat systematically, unlike trends, seasonality, or cycles.
21. Which of the following best describes forecasting in time series analysis?
A. Predicting unexpected events
B. Estimating past variations
C. Identifying random shocks
D. Predicting future values based on past data
Forecasting is the process of predicting future values of a variable using historical time series data and statistical models.
22. Which of the following forecasting methods is considered a quantitative technique?
A. Delphi Method
B. Moving Average Method
C. Expert Opinion
D. Brainstorming
Moving Average Method is a quantitative technique based on numerical data. Delphi, Expert Opinion, and Brainstorming are qualitative forecasting methods.
23. Which forecasting technique fits a straight line to the data by minimizing the sum of squared errors?
A. Least Squares Method
B. Exponential Smoothing
C. Ratio-to-Moving-Average Method
D. Semi-Average Method
The Least Squares Method fits a trend line such that the sum of squared deviations between actual and predicted values is minimized.
24. In exponential smoothing forecasting, the smoothing constant (α) lies between:
A. –1 and +1
B. 0 and 2
C. 0 and 1
D. Greater than 1
The smoothing constant α in exponential smoothing ranges between 0 and 1. A higher α gives more weight to recent data, while a lower α gives more weight to past data.
25. Which of the following is an advantage of using forecasting techniques in banking?
A. Eliminates uncertainty in business
B. Guarantees 100% accuracy of predictions
C. Prevents all risks in lending
D. Helps in better planning of credit, investments, and liquidity
Forecasting techniques help banks anticipate future trends in deposits, credit demand, and liquidity needs, improving strategic planning. However, they do not guarantee perfect accuracy.
26. The sales of a product for 5 years are: 200, 220, 240, 260, 280. Using a 3-year moving average, the forecast for Year 6 is:
A. 250
B. 255
C. 260
D. 265
3-year MA for Year 6 = (240 + 260 + 280) ÷ 3 = 780 ÷ 3 = 260.
27. A company wants to fit a straight-line trend Y = a + bX using Least Squares. Data: Year (X): 1, 2, 3, 4; Sales (Y): 10, 12, 14, 16. What is the forecast for Year 5?
A. 16
B. 17
C. 18
D. 20
Trend line = Y = a + bX.
Here, the increase is consistent (+2 each year). Equation: Y = 8 + 2X.
For Year 5 (X=5), Y = 8 + (2×5) = 18. Correct answer = C.
28. If last year’s forecast was 500 units, actual demand was 550 units, and smoothing constant α = 0.2, then exponential smoothing forecast for this year is:
