Step 1: Assign Weights<\/strong><\/p>\n<\/p>\n
The first step to finding a weighted value average is to assign weights to each value in your dataset. These weights represent the significance or importance of each value. The sum of all weights should be equal to 1 or 100%.<\/p>\n
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Step 2: Multiply Values with Respective Weights<\/strong><\/p>\n<\/p>\n
Next, multiply each value by its corresponding weight. This step ensures that values with higher weights contribute more to the overall average.<\/p>\n
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Step 3: Add the Weighted Values<\/strong><\/p>\n<\/p>\n
Sum up all the weighted values calculated in the previous step. This total represents the weighted sum of all values.<\/p>\n
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Step 4: Calculate the Weighted Value Average<\/strong><\/p>\n<\/p>\n
Finally, divide the weighted sum of values obtained in step 3 by the total sum of weights. This calculation provides the weighted value average.<\/p>\n
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Let’s illustrate this process with an example:<\/p>\n
Suppose we have a dataset of three values: 10, 15, and 20. We assign weights of 0.2, 0.3, and 0.5 to these values, respectively. Following the steps mentioned above:<\/p>\n
Step 1:<\/strong> Weights assigned: 0.2, 0.3, 0.5<\/p>\n<\/p>\n
Step 2:<\/strong> Multiply each value by its respective weight:<\/p>\n<\/p>\n
10 x 0.2 = 2<\/p>\n
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15 x 0.3 = 4.5<\/p>\n
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20 x 0.5 = 10<\/p>\n
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Step 3:<\/strong> Add the weighted values:<\/p>\n<\/p>\n
2 + 4.5 + 10 = 16.5<\/p>\n
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Step 4:<\/strong> Calculate the weighted value average:<\/p>\n<\/p>\n
16.5 \/ (0.2 + 0.3 + 0.5) = 16.5 \/ 1 = 16.5<\/p>\n
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Therefore, the weighted value average of the given dataset is 16.5.<\/p>\n