How to calculate simple statistics

In statistics, the most important calculations are the mean, mode, median, variance, and standard deviation (std dev) 

In this hub, I will cover the following:

• sample size
• population
• mean
• mode
• median
• variance
• standard deviation

Statistics begins with a set of numbers which are called the sample.

The set of all possible numbers is called the population.

Let's say that we ask 5 friends to rate a popular movie on the scale from 1 to 10.

Then, the sample size is 5 and the population is the set of all people who have seen or will see the movie.

So, we ask our 5 friends to rate and movie and here's what we get:

Fred: 6

Sally: 9

Michael: 8

Raul: 9

Elena: 2

To calculate the mean, you sum up all the numbers in the sample and then divide by the sample size. The sum is 5+10+8+9+2= 34. Since the sample size is 5, the mean is 34/5 = 6.8.

This then is the average of the sample.

The mode is the number that appears the most often in the sample.

To calculate the mode, we count the number of times each rating is made. So we have one 6, two 9's, one 8, and one 2. Since we have two 9's and one of everything else, 9 is the mode.

But what would happen if we have the following sequence: 2,2,8,9,9?

In this case, we would say that there is no unique mode. A mode is unique if and only if one number is more frequent than all others.

The median is the value we get when we order all of our numbers and then find the one in the middle.

If we order the numbers from smallest to largest, we get: 2, 6, 8, 9, 9

Since we have a sample size of 5, the number in the middle is 8.

But what happens if the sample size is even. In this case, we can add the two middle numbers and divide by 2.

So, if our numbers are: 2,6,8,9, then the median is (6+8)/2 = 7.

The variance is a measure of the variation of the sample data. The larger the variance, the more random the answers appear. Many people find standard deviation to be a more useful measure of variability.

The method for calculating the variance is different depending on whether we are calculating the variance of a population (everyone) or the variance of a sample (some but not all).

Here are the steps:

(1) Figure out the mean. This is the sum of the numbers given divided by the sample size (i.e. the average).

(6+ 9+ 8 + 9 + 2)/5 = 34/5 = 6.8

(2) Figure out the difference between each number and its mean so that we have:

(6 - 6.8), (9 - 6.8), (8 - 6.8), (9 - 6.8), (2 - 6.8) = -0.8, 2.2, 1.2, 2.2, -4.8

(3) Get the square of each difference in step #2 so that we have:

(-0.8)*(-0.8), (2.2)*(2.2), (1.2)*(1.2), (2.2)*(2.2), (-4.8)*(-4.8) = 0.64, 4.84, 1.44, 4.84, 23.04

(4) Get the sum of all the squares in step #3 so that we have:

sum of squares = 0.64 + 4.84 + 1.44 + 4.84 + 23.04 = 34.8

(5) Now, for the sample variance, we divide the sum in step #4 by the sample size - 1

Variance = 34.8/(5-1) = 34.8/4 = 8.7

The standard deviation, like variance, is a measure of the variation of the sample data. The larger the standard deviation, the more random the answers appear.  Standard deviation is more popular as a measure than variance.

The method for calculating the standard deviation is different depending on whether we are calculating the variance of a population (everyone) or the variance of a sample (some but not all).  The method is the same as variance with one additional step. 

Here are the steps:

(1) Figure out the mean. This is the sum of the numbers given divided by the sample size (i.e. the average).

(6+ 9+ 8 + 9 + 2)/5 = 34/5 = 6.8

(2) Figure out the difference between each number and its mean so that we have:

(6 - 6.8), (9 - 6.8), (8 - 6.8), (9 - 6.8), (2 - 6.8) = -0.8, 2.2, 1.2, 2.2, -4.8

(3) Get the square of each difference in step #2 so that we have:

(-0.8)*(-0.8), (2.2)*(2.2), (1.2)*(1.2), (2.2)*(2.2), (-4.8)*(-4.8) = 0.64, 4.84, 1.44, 4.84, 23.04

(4) Get the sum of all the squares in step #3 so that we have:

sum of squares = 0.64 + 4.84 + 1.44 + 4.84 + 23.04 = 34.8

(5)  We divide the sum in step #4 by the sample size - 1

34.8/(5-1) = 34.8/4 = 8.7

(6)  Last, we take the square root of the value in step #5.

Standard Deviation = sqrt(8.7) = roughly 2.95 

A smaller standard deviation means that there is more agreement between the numbers (less variation)and a larger standard deviation means that there is less agreement (more variation).

If the observations are random and fall in a bell curve, then we can use the standard deviation to make the following observations:

• 68% of the numbers lie within one standard deviations of the mean
• 95% of the numbers lie within two standard deviations of the mean

Now, movie ratings are, in theory, not random since they are based on the quality of a movie. Additionally, we can know that 100% are between 1 and 10 and are most likely whole numbers.

But, what would it say for another movie if the mean were 5 and the standard deviation was 1 and we assume that ratings form a bell curve.

With this information, we can expect:

• 68% of all people will rate the movie between 4 and 6 since 4= 5-1 and 6 = 5+1
• 95% of all people will rate the movie between 3 and 7 since 3 = 5 - 2*1 and 7 = 5 + 2*1