# Statistics Calculator

Efficiently analyze and calculate statistical data using our Statistics Calculator. Compute measures such as mean, median, standard deviation, and more. Simplify complex statistical calculations and make data-driven decisions.

Above is a simple, generalized statistics calculator that computes statistical values such as the mean, population standard deviation, sample standard deviation, and geometric mean among others. Many of these values are more well described in other calculators also available on this website. Visit the hyperlinks provided for more detail on how to calculate these values, as well as basic examples and applications of each. Note that while the computation of variance is not explicitly shown, it is calculated as the standard deviation squared, or **σ ^{2}**. Simply ensure that the correct standard deviation is being used (

**s**vs.

**σ**) and square the value to obtain the variance.

### Geometric Mean

The geometric mean in mathematics is a type of average that uses the product of the values in a set to indicate central tendency. This is in contrast to the arithmetic mean that performs the same function using the sum of the values in the set rather than their products. The geometric mean is useful in cases where the values being compared vary largely. Imagine a car that is rated on a scale of 0-5 for fuel efficiency, and a scale of 0-100 for safety. If the arithmetic means were used, the safety of the vehicle would be given far more weight, since a small percentage change on a larger scale will result in a larger difference than a large percentage change on a smaller scale; a change of fuel efficiency rating from 2 to 5 which is a 250% increase in rating would be overshadowed by a 6.25% rating change of 80 to 85 if only the arithmetic mean were considered. The geometric mean accounts for this by normalizing the ranges being averaged, resulting in none of the ranges dominating the weighting. Unlike the arithmetic mean, any given percentage change in the geometric mean has the same effect on the geometric mean. The equation for calculating the geometric mean is as follows:

In the equation above, **i** is the index that refers to the location of a value in a set, **x _{i}** is an individual value, and

**N**is the total number of values.

**i=1**refers to the starting index, i.e. for a data set 1, 5, 7, 9, 12,

**i=1**is 1,

**i=2**is 5,

**i=3**is 7, and so on. The notation above essentially means to multiply each value in the set through the

**n**value, and then take the

^{th}**n**root of the product. Refer to the root calculator if necessary for a review of

^{th}**n**roots. Below is an example using the listed data set:

^{th}The geometric mean has applications within proportional growth, the social sciences, aspect ratios, geometry, and finance among others, and like most other statistical values, can provide highly useful information when used in the proper contexts.

### Statistics Calculator Example

Data Set | 10 | 15 | 12 | 17 | 20 |
---|---|---|---|---|---|

Mean | 14.8 | ||||

Median | 15 | ||||

Mode | None | ||||

Range | 10 | ||||

Variance | 11.7 | ||||

Standard Deviation | 3.42 | ||||

Sum | 74 | ||||

Minimum | 10 | ||||

Maximum | 20 |

In this example, we have a data set consisting of five numbers: 10, 15, 12, 17, and 20.

To calculate the mean, you would sum up all the numbers in the data set and divide by the total count. In this case, (10 + 15 + 12 + 17 + 20) / 5 = 14.8. So, the mean is 14.8.

To find the median, you arrange the numbers in ascending order and select the middle value. Since we have an odd number of values, the middle value is 15. Thus, the median is also 15.

The mode represents the most frequently occurring value(s) in the data set. In this example, there is no value that appears more than once, so the mode is none.

To calculate the range, you subtract the minimum value from the maximum value. In this case, 20 - 10 = 10. So, the range is 10.

The variance is a measure of how spread out the numbers in the data set are. It is calculated by finding the average of the squared differences between each number and the mean. In this example, the variance is 11.7.

The standard deviation is the square root of the variance. So, the standard deviation for this data set is approximately 3.42.

The sum simply represents the total of all the numbers in the data set, which in this case is 74.

Lastly, the minimum and maximum values in the data set are 10 and 20, respectively.

You can use this table as a guide to calculate similar statistics for other data sets by replacing the values in the "Data Set" column with your own set of numbers.