Simple and Weighted Averages - Measures of Central Tendency, Business Mathematics & Statistics

# Simple and Weighted Averages - Measures of Central Tendency, Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com

115 videos|142 docs

## FAQs on Simple and Weighted Averages - Measures of Central Tendency, Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com

 1. What is a simple average?
Ans. A simple average, also known as the arithmetic mean, is a measure of central tendency that is calculated by summing up all the values in a dataset and dividing it by the total number of values. It is commonly used to find the average of a group of numbers.
 2. How is a weighted average different from a simple average?
Ans. Unlike a simple average, a weighted average takes into account the importance or significance of each value in a dataset. Each value is assigned a weight, which is multiplied by the value itself before calculating the average. This means that certain values have more influence on the final average than others.
 3. When should I use a simple average?
Ans. A simple average is typically used when all the values in a dataset are equally important and have the same weight. It provides a balanced representation of the data without giving more weight to any particular value. Simple averages are commonly used in situations such as calculating test scores, average daily temperatures, or average prices.
 4. In what situations would a weighted average be more appropriate?
Ans. Weighted averages are useful when different values in a dataset have varying degrees of importance or significance. For example, in financial calculations, such as calculating portfolio returns, different investments may have different weights based on their value or risk. Weighted averages are also used in situations where certain data points are more reliable or accurate than others.
 5. How can I calculate a weighted average?
Ans. To calculate a weighted average, you need to assign weights to each value in the dataset. Multiply each value by its corresponding weight, sum up all the weighted values, and then divide the sum by the total of all the weights. The formula for calculating a weighted average is: Weighted Average = (Value1 * Weight1 + Value2 * Weight2 + ... + ValueN * WeightN) / (Weight1 + Weight2 + ... + WeightN).

115 videos|142 docs

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