When index number is calculated for several variables, it is called:a)...
⇒ When index number is calculated for several variables, it is called : Composite Index.
⇒ A composite index number is formed by combining two or more index numbers, and a weighting is usually given to each of the indexes in order to calculate the weighted average index number.
⇒ A composite index number is a number that measures an average relative change in a group of relative variables with respect to a base.
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When index number is calculated for several variables, it is called:a)...
Understanding Composite Index
A composite index is a statistical measure that aggregates multiple variables into a single index number. This approach is particularly useful in economic and financial analysis, where various indicators need to be evaluated together to understand broader trends.
Key Features of a Composite Index:
- Multidimensional Analysis: Unlike a simple index that measures a single variable, a composite index considers several variables. This allows for a more comprehensive view of the data being analyzed.
- Weighting of Variables: In a composite index, each variable can be assigned a different weight based on its importance. This reflects the relative contribution of each variable to the overall index.
- Applications: Composite indices are commonly used in various fields, including economics (e.g., Consumer Price Index), finance (e.g., stock market indices), and social sciences (e.g., Human Development Index).
Examples of Composite Indices:
- Consumer Price Index (CPI): Measures the average change over time in the prices paid by consumers for a basket of goods and services.
- Human Development Index (HDI): Combines indicators of life expectancy, education, and per capita income to assess the development of countries.
Conclusion:
A composite index is a powerful tool for summarizing complex data involving multiple variables. By aggregating these variables into one index, analysts can derive more insightful conclusions about trends and patterns in the data. This is why the correct answer to the question is option 'B'—composite index.