Average of four consecutive odd numbers is 106. What is the third number in ascending order? 

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Could you find the third odd number in a row where the average of four consecutive odd numbers is 106? Just figure out the third number in order, and you’ve cracked the code! Check out our guide.

Average of four consecutive odd numbers is 106. What is the third number in ascending order?

Let’s call the first odd number “x”. Then, the next three odd numbers in ascending order would be x + 2, x + 4, and x + 6.

We know the average of these four numbers is 106. So, we can set up the following equation:

(x + (x + 2) + (x + 4) + (x + 6)) / 4 = 106

Combining like terms and simplifying the equation, we get:

4x + 12 = 424

Subtracting 12 from both sides and then dividing both sides by 4, we find:

x = 103

Since x is the first odd number, the third odd number in ascending order is x + 4, which is equal to:

103 + 4 = 107

Therefore, the third odd number in ascending order is 107.

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What is an Average in Mathematics?

In mathematics, the term “average” usually refers to the mean, which is a way to summarize a set of numerical data by finding a single representative value. It’s essentially the sum of all the values divided by the number of values.

Here’s a breakdown:

Definition:

  • The average (mean) is the ratio of the sum of all the values in a set to the total number of values.
  • It gives you an idea of the “typical” value within the set.

Formula:

  • The average (mean) is calculated using the following formula:

average = (sum of all values) / (number of values)

Example:

  • Let’s say you have the following set of numbers: 2, 5, 8, 10
  • To find the average, you would add all the numbers together: 2 + 5 + 8 + 10 = 25
  • Then, divide the sum by the number of numbers: 25 / 4 = 6.25
  • Therefore, the average (mean) of the set is 6.25.

The average is just one way to summarize data. There are other measures of central tendency like the median (middle value) and the mode (most frequent value).The average can be sensitive to outliers (extreme values) in the data. In such cases, other measures like the median might be more appropriate.

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