Which of the following statements are correct?
(A).When a cyclical pattern in data has a period of less than 1 year, the pattern in data is called seasonal variation
(B). When a cyclical pattern has a period more than 1 year, we refer to it as cyclical variation
(C). Seasonality is considered equivalent to forecasting
(D). Cyclical behaviour in business is also termed as business cycle
Choose the correct answer from the options given below:
Understanding Data Patterns: Seasonality and Cycles
This question asks us to evaluate the correctness of four statements related to patterns found in data, particularly focusing on seasonal variation, cyclical variation, and the business cycle. Let's analyze each statement:
Statement (A): Seasonal Variation Definition
Statement (A) claims that when a cyclical pattern in data has a period of less than 1 year, it's called seasonal variation. This is the standard definition. Seasonal patterns repeat within a year, like daily, weekly, or monthly fluctuations that are consistent within each year.
- Example: Ice cream sales peaking in summer months every year.
- Period: Less than or equal to one year (e.g., quarterly, monthly).
Therefore, statement (A) is correct.
Statement (B): Cyclical Variation Definition
Statement (B) states that when a cyclical pattern has a period of more than 1 year, it's referred to as cyclical variation. This definition accurately describes cyclical patterns that are longer-term and not tied strictly to the calendar year. These patterns often relate to economic or other long-term fluctuations.
- Example: Economic booms and recessions spanning several years.
- Period: More than one year.
Thus, statement (B) is correct.
Statement (C): Seasonality vs. Forecasting
Statement (C) suggests that seasonality is considered equivalent to forecasting. This is incorrect. Seasonality is a specific type of pattern (a repeating cycle within a year) identified within historical data. Forecasting, on the other hand, is the process of predicting future values based on historical data, which may include seasonality, trends, and cycles, but is a broader activity.
- Seasonality: A characteristic of the data (pattern).
- Forecasting: A process using data characteristics to predict the future.
Seasonality is a component that can be *used* in forecasting, but they are not the same thing. Therefore, statement (C) is incorrect.
Statement (D): Cyclical Behaviour and Business Cycle
Statement (D) posits that cyclical behaviour in business is also termed the business cycle. This is accurate. The term 'business cycle' specifically refers to the economy-wide fluctuations in production and consumption that occur over periods of time, typically characterized by alternating phases of expansion and contraction, which fits the definition of cyclical variation in an economic context.
- The business cycle represents long-term economic fluctuations.
- It is a prime example of cyclical variation.
Therefore, statement (D) is correct.
Conclusion
Based on the analysis of each statement:
- Statement (A) is correct.
- Statement (B) is correct.
- Statement (C) is incorrect.
- Statement (D) is correct.
The correct statements are (A), (B), and (D). This corresponds to the option stating "(A), (B) and (D) only".
Important Questions from Elementary Statistics (Notes)
Let $X_1, X_2, X_3$ be a random sample of size 3 from an absolutely continuous distribution that is symmetric about 0. For $i=1,2,3$, let $R_i$ denote the rank of $|X_i|$ among $|X_1|, |X_2|$ and $|X_3|$.
If $T^+ = \sum_{i=1, X_i>0}^3 R_i$
is the Willcoxon signed-rank statistic, then which of the following statements are true?,
- Which of the following is the first step in calculating the median of data set?
1. Average the middle two values of the data set
2. Array the data
3. Determine the relative weights of the data values in terms of importance
4. Find the average distance of the observations in the data set from the mean - The sum of deviations of the items from __________ ignoring signs is the least?
- The relationship between mean, median and mode is:
Match List-I with List-II
List-1 List-II Methods to Deseasonalise the Time Series Underlying Meaning (A). Method of simple average (I). It assumes that seasonal variation for a given month is constant fraction of trend (B). Ratio to Trend Method (II). It is the easiest method of obtaining a seasonal index (C). Ratio to moving average method (III). It is the most difficult method of measuring seasonal variations (D). Link relative method (IV). It is also known as the percentage of moving average method
Choose the correct answer from the options given below:
