Weighted Mean Formula - Examples, Relevance, Vs Mean (2024)

What is Weighted Mean?

The weighted mean equation is a statistical method that calculates the average by multiplying the weights with their respective mean and taking its sum. It is a type of average in which weights assign individual values to determine the relative importance of each observation. The weighted mean formula statistics are useful across sectors such as finance, education, and economics.

Weighted Mean Formula - Examples, Relevance, Vs Mean (1)

The weighted mean allows for the incorporation of varying degrees of importance or significance among data points in a dataset. By assigning weights to each value, the weighted mean reflects the relative importance of different elements, making it a valuable tool in situations where certain values carry more weight or relevance than others.

Table of contents
  • What is Weighted Mean?
    • Weighted Mean Formula Explained
    • Formula
    • How To Calculate?
    • Examples
    • Relevance and Uses
    • Weighted Mean Vs Mean
    • Frequently Asked Questions (FAQs)
    • Recommended Articles
  • The weighted mean equation is a statistical approach for calculating the average by multiplying the weights with their respective mean and taking its sum.
  • It is a type of average where weights are assigned individual values to find each observation's relative importance.
  • One may determine the weighted mean by multiplying the weight with the quantitative outcome and adding all the products. If all the weights are equal, then the weighted and arithmetic mean are the same.
  • The weighted mean may help an individual make decisions where some characteristics have more significance than others.

Weighted Mean Formula Explained

The weighted mean, also known as the weighted average, is a statistical measure that calculates the average of a set of numbers, where each number is assigned a weight indicating its relative importance or contribution to the overall average. Unlike the simple arithmetic mean, where each value carries equal weight, the weighted mean assigns different weights to each value based on predetermined criteria.

To calculate the average weighted mean formula, one multiplies each value by its corresponding weight and then divides the sum of these products by the sum of the weights. This method allows for the prioritization of certain values over others, reflecting their significance or relevance in the context of the data set.

Weighted means are commonly used in various fields, such as finance, economics, and education, where certain data points may carry more significance than others. For example, in financial analysis, the weighted mean may be used to calculate the average return on investment in a portfolio, with each investment's weight reflecting its proportion of the total portfolio value.

In educational settings, teachers may use weighted means to calculate final grades, assigning different weights to exams, quizzes, and homework assignments based on their importance in assessing student performance. Similarly, in economic analysis, the weighted mean may be used to calculate composite indices, such as the Consumer Price Index (CPI), where the weights reflect the relative importance of different goods and services in measuring inflation.

Overall, the weighted mean provides a flexible and customizable approach to calculating averages, allowing analysts to account for varying degrees of importance or significance among the data points in a given dataset.

Formula

The weighted mean formula statistics are calculated by multiplying the weight with the quantitative outcome and adding all the products. If all the weights are equal, then the weighted mean and arithmetic mean will be the same.

Weighted Mean = ∑ni=1 (xi*wi)/∑ni=1wi

It implies thatWeighted Mean = w1x1+w2x2+…+wnxn/w1+w2+…+wn

Where

  • ∑ denotes the sum
  • w is the weights and
  • x is the value

In cases where the sum of weights is 1,

Weighted Mean = ni(xi* wi)

How To Calculate?

Let us understand the step-by-step process of calculating the average weighted mean formula through the points below.

  1. List the numbers and weights in tabular form. Presentation in tabular form is not compulsory but makes the calculations easy.
  2. Multiply each number and the relevant weight assigned to that number (w1by x1,w2by x2,and so on).
  3. Add the numbers obtained in Step 2 (∑x1wi).
  4. Find the sum of the weights (∑wi).
  5. Divide the total of the values obtained in Step 3 by the sum of the weights obtained in Step 4 (∑x1wi/∑wi).

Note: If the sum of the weights is 1, then the total of the values obtained in Step 3 will be the weighted mean.

Examples

Now that we understand the basics of weighted mean formula statistics, let us also understand the practicality of the concept through the examples below.

Example #1

The following are 5 numbers and the weights assigned to each number. Next, calculate the weighted mean of the above numbers.

Solution:

Weighted Mean Formula - Examples, Relevance, Vs Mean (2)
Weighted Mean Formula - Examples, Relevance, Vs Mean (3)
Weighted Mean Formula - Examples, Relevance, Vs Mean (4)

WM will be -

Weighted Mean Formula - Examples, Relevance, Vs Mean (5)

Example #2

The CEO of a company has decided that he will continue the business only if the return on capital is more than the weighted average cost of capital. The company makes a return of 14% on its capital. The capital consists of equity and debt at 60% and 40%, respectively. The cost of equity is 15%, and the cost of debt is 6%. Advise the CEO on whether the company should continue with its business.

Solution:

Let us first present the given information in tabular form to understand the scenario.

We will use the following data for the calculation.

Weighted Mean Formula - Examples, Relevance, Vs Mean (6)
Weighted Mean Formula - Examples, Relevance, Vs Mean (7)

WM =0.60*0.15 + 0.40*0.06

= 0.090 + 0.024

Weighted Mean Formula - Examples, Relevance, Vs Mean (8)

Since the return on capital at 14% is more than the weighted average cost of capital of 11.4%, the CEO should continue with his business.

Example #3

It is difficult to gauge the future economic scenario. The stock returns could get affected. The finance advisor develops different business scenarios and expected stock returns for each scenario. Therefore, it would enable him to make a better investment decision. Calculate the weighted mean average from the above data to help the investment advisor showcase the expected stock returns to his clients.

Solution:

We will use the following data for the calculation.

Weighted Mean Formula - Examples, Relevance, Vs Mean (9)
Weighted Mean Formula - Examples, Relevance, Vs Mean (10)
Weighted Mean Formula - Examples, Relevance, Vs Mean (11)

=0.20*0.25 + 0.30*(-0.10) + 0.50*0.05

= 0.050 – 0.030 + 0.025

WM will be -

Weighted Mean Formula - Examples, Relevance, Vs Mean (12)

The expected return for the stock is 4.5%.

Example #4

Jay is a rice merchant who sells various types of rice in Maharashtra. Some rice grades are of higher quality and sold at a higher price. He wants you to calculate the weighted mean from the following data:

Solution:

We will use the following data for the calculation.

Weighted Mean Formula - Examples, Relevance, Vs Mean (13)

Step 1:In Excel, there is an inbuilt formula for calculating the products of the numbers and their sum, which is one of the steps in calculating the weighted mean. Select a blank cell and type this formula = SUMPRODUCT(B2: B5, C2: C5), where the range B2: B5 represents the weights and the range C2: C5 represents the numbers.

Weighted Mean Formula - Examples, Relevance, Vs Mean (14)

Step 2:Calculate the sum of the weights using the formula =SUM(B2: B5), where the range B2: B5 represents the weights.

Weighted Mean Formula - Examples, Relevance, Vs Mean (15)

Step 3: Calculate =C6/B6,

Weighted Mean Formula - Examples, Relevance, Vs Mean (16)
Weighted Mean Formula - Examples, Relevance, Vs Mean (17)

WM will be -

Weighted Mean Formula - Examples, Relevance, Vs Mean (18)

It gives the WM as Rs 51.36.

Relevance and Uses

Weighted mean can aid an individual in making decisions where some attributes have more significance than others. For instance, one generally uses it to calculate a specific course's final grade. In courses, the comprehensive exam typically has more weight on the grade than chapter tests. Thus, if one performs poorly in chapter tests but does well in final exams, the weighted average of the grades will be relatively high.

One may use it in descriptive statistical analysis, such as calculating index numbers. For instance, stock market indices such as Nifty or BSE Sensex are computed using the weighted average method. One can also apply it in physics to find the center of mass and moments of inertia of an object with a known density distribution.

People in business often calculate the average weighted mean formula to evaluate the average prices of goods purchased from different vendors where the quantity is considered the weight. It gives a businessman a better understanding of his expenses.

One can apply the weighted mean formula to calculate the average returns from a portfolio comprising different financial instruments. For instance, let us assume equity consists of 80% of a portfolio and debt balance 20%. The returns from equity are 50% and from debt are 10%. The simple average would be (50%+10%)/2, which is 30%.

It gives a wrong understanding of the returns, as equity constitutes most of the portfolio. Hence, we calculate a weighted average, which works out to be 42%. This number of 42% is much closer to equity returns of 50%, as equity accounts for most of the portfolio. In other words, the returns pull by an equity weight of 80%.

Weighted Mean Vs Mean

Let us understand the differences between weighted mean and mean through the comparison below.

Weighted Mean

  • Incorporates weights assigned to each value based on their relative importance or contribution.
  • Calculated by multiplying each value by its corresponding weight and dividing the sum of these products by the sum of the weights.
  • Useful when certain values have more significance or relevance than others in the dataset.
  • Commonly used in finance, economics, and education to calculate averages where some data points carry more weight.

Mean

  • A simple average is calculated by summing up all values and dividing by the total number of values.
  • Treats each value equally without considering their relative importance or contribution.
  • Suitable for datasets where all values have equal significance.
  • Widely used in basic statistical analysis and everyday calculations.
  • It may not accurately reflect the true average when certain values significantly deviate from the others or have varying degrees of importance.

Frequently Asked Questions (FAQs)

How to use the weighted mean formula?

The weighted mean is calculated by multiplying the weight or probability connected with a specific event or results with the quantitative outcome and then combining all the products.

How to get the weighted mean formula?

The formula for calculating the weighted average is the sum of all the variables multiplied by their weight. Then, one must divide it by the sum of the weights.

Can I use the weighted mean formula for non-numerical data?

The weighted mean formula is typically used for numerical data. If you have non-numerical data, you may need to assign numerical values or scores to each category or use alternative methods for calculating the average.

Where is the weighted average used?

Weighted averages are used in statistical analysis, stock portfolios, and teacher grading averages. Moreover, it is an essential tool in accounting for stock fluctuations, uneven or misrepresented data, and assuring the same data points are equal in the represented proportion.

Recommended Articles

This article is a guide to Weighted Mean Formula. Here, we discuss how to calculate Weighted Mean, examples, relevance & uses, and downloadable Excel template. You can learn more about Excel modeling from the following articles: -

  • Arithmetic Mean Formula
  • What are Weighted Average Shares Outstanding?
  • Average vs. Weighted Average
  • Mean vs. Median
Weighted Mean Formula - Examples, Relevance, Vs Mean (2024)

FAQs

What is the relevance of weighted mean in research? ›

Weighted mean plays a crucial role in the statistical treatment of data by providing a more accurate representation of the data when certain observations carry more significance than others.

What is the formula for weighted mean in research example? ›

Calculating the weighted average involves multiplying each data point by its weight and summing those products. Then sum the weights for all data points. Finally, divide the weight*value products by the sum of the weights. Voila, you've calculated the weighted mean!

When should you use the weighted mean instead of the regular mean? ›

You should use a weighted average when you want to assign more importance to some numbers in a dataset than others.

Is there a difference between mean and weighted mean? ›

Answer and Explanation:

Mean is used when the statistician considers each score in the data value of the same or similar importance. On the other hand, the weighted mean is used when the statistician considers one value to have higher importance than the other.

How to interpret data using weighted mean? ›

In a weighted mean, each data point value is multiplied by the assigned weight which is then summed and divided by the sum of weights. A weighted mean reflects the relative importance of each observation and is thus more descriptive than a simple mean.

What is the weighted mean difference in research? ›

In a meta-analysis, when study results measured using the same scale are being combined, the difference between two means, weighted by the precision of the study. Note: The precision of the study's estimate of effect may, for example, correspond to the inverse of the variance.

In what situation would a weighted mean be used? ›

Weighted means are useful in a wide variety of scenarios. For example, a student may use a weighted mean in order to calculate his/her percentage grade in a course. In such an example, the student would multiply the weighing of all assessment items in the course (e.g., assignments, exams, projects, etc.)

Why do you need to do a weighted average calculation instead of a regular average? ›

A weighted average is sometimes more accurate than a simple average. In a weighted average, each data point value is multiplied by the assigned weight, which is then summed and divided by the number of data points. A weighted average can improve the data's accuracy.

What are the disadvantages of weighted average method? ›

The disadvantages of using weighted average are that it does not reflect the actual flow or replacement of goods, it may not capture the true profitability or efficiency of the business, and it may not be suitable for businesses that sell unique or perishable items.

What are the disadvantages of weighted mean in statistics? ›

One of the primary limitations of weighted averages is that they are not suitable for all types of data. For example, if you have a dataset with extreme outliers, the weighted average may not be an accurate representation of the data. In such cases, the median or mode may be a better measure of central tendency.

What is the advantage of weighted mean? ›

The weighted mean helps us in finding a more accurate average by considering the weight of each value instead of only adding up individual values. Arithmetic mean is an integral statistical value used in multiple everyday purposes to make the interpretation of data easier.

Why is weighted mean less than mean? ›

The weighted mean is similar to an ordinary arithmetic mean, except that instead of each of the data points contributing equally to the final average, some data points contribute more than others. If all the weights are equal, then the weighted mean is the same as the mean.

What is a weighted mean statistical tool in research sample? ›

The weighted mean involves multiplying each data point in a set by a value which is determined by some characteristic of whatever contributed to the data point. An example should help make that rather vague definition clearer.

When would a researcher calculate a weighted mean? ›

The weighted mean is used to compute the combined mean for two or more samples of scores in which the number of scores in each sample is disproportionate or unequal. The weighted mean is heavier than an arithmetic mean.

Why use weighted mean in Likert scale? ›

This provides a more nuanced and accurate representation of the respondents' opinions or attitudes. Weighted means can be particularly useful when analyzing Likert scale data in research or survey studies, as they allow for a more comprehensive understanding of the data.

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