Understand Mean, Mode, Median Formulas


A central tendency measure is defined as a single value that attempts to describe a set of data by identifying the central position within that data set. The other name for central tendency measures is central location measures and they are generally referred to as summary statistics. The mean, median, and mode are probably the most well-known measure of central tendency. In this article, we are going to discuss mean, mode, median.

Purpose of Mean, Mode, Median

We’re all fans of cricket, but have you ever wondered why the run rate of a particular over is projected during a game, and what the run rate means? Alternatively, when you receive your examination results card, you mention the aggregate percentage. What, once again, is the definition of aggregate? In real life, all of these quantities make it simple to represent a collection of data in terms of a single value. It’s known as Statistics.

Consider a 50-over One-Day International (ODI) match between India and Australia. By the end of the first innings, India had scored 370 runs. How do you determine whether India scored well or poorly? It’s pretty straightforward, right? You find the overall run rate that is appropriate for such a score. As a result, the concepts of mean, median, and mode enter the picture.

Do You Know These Formulas

Mean Formula

The sum of the observations divided by the total number of observations is the mean formula. This will be useful in resolving the vast majority of arithmetic mean-related problems. The mean formula for the given observations is as follows:

Mean Formula = (Sum of Observations) divided by (Total Numbers of Observations)

Median Formula

In general, the median represents the middle value of a given set of data when arranged in a specific order.

Mode Formula

The mode is defined as the most frequently occurring number in the data set.

For example- here is a list of the marks secured by students of a class- 10,9,10,8,7

The mode will be equal to 10 since the occurrence of 10 is twice.

Median vs. Mean

  • Both are measures of where the center of a data set is (referred to as “Central Tendency” in statistics), but they are usually different numbers. Consider the following number sequence: 10, 10, 20 , 40 , 70
  • First, you need to calculate the mean by adding all of the numbers and then dividing by the number of items in the set: 10 + 10 + 20 + 40 + 70 / 5 which equals 30.
  • The median is determined by sorting the set from lowest to highest and locating the exact middle. The median is simply the number in the middle: 20.
  • Sometimes the two numbers will be the same. For example, the data set 1 + 2 + 4 + 6 + 7 / 5 equals 4 has a mean of 1 + 2 + 4 + 6 + 7 / 5 equals 4 and a median (middle) of 4.

Average vs. Mean – What’s the Difference?

When you were younger, you were probably taught that an average was a “middling” amount for a set of numbers. Now, you added the numbers, divided them by the number of items you can fit in your cart, and voila! you have the average. For instance, the sum of 10, 5, and 20 is: 10 + 6 + 20 = 36 / 3 = 12.

Then you started studying statistics, and the “average” became known as the mean. What transpired? The answer is that they both mean the same thing (they are synonyms).

However, technically, the word mean is an abbreviation for the arithmetic mean. We use different words in statistics because there are many different types of means, each of which performs a different function.

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Kimberly Atwood’s books have received starred reviews in Publishers Weekly, Library Journal, and Booklist. Kimberly lives in the Rocky Mountains with her husband, an exceptionally perfect dog, and an attack cat. Before she started writing historical research, Kimberly got a graduate degree in theoretical physical chemistry from Ohio State University. After that, just to shake things up, she went to law school at the University of London and graduated summa cum laude. Then she did a handful of clerkships with some really important people who are way too dignified to be named here. She was a law professor for a while. She now writes full-time.

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