## Combinations

Combinations are sets of objects that are unordered. Permutations were concerned with order. In a permutation the values 1234, 2341, 3412 and 4321 are treated as different. However, in Combinations, they are treated as 1 result. If you’re curious about the Latex Markdown to create the equation above, it is Continue Reading

## Permutations

A permutation is a calculation of how many ways a set can be represented. This is a simple factorial of the number of the entire set. Meaning if we had a set of values: However the formula changes as we get into more complex problems. Consider this example on BetterExplained.com: Continue Reading

## Probability Question

Taken from the Udemy course Probability & Statistics for Business and Data Science. Consider the following question: “A company made a total of 50 trumpet valves. It is determined that one of the values (of 50) was defective. If three valves are used in a trumpet, what is the probability Continue Reading

## Measures of Dispersion

To get an idea of the shape of data, we can’t use Mean, Median or Mode. Instead the Measurements of Dispersion are used, which are done with the following functions: Range Standard Deviation Variance Range Simply this is the literal range, if we were measuring heights of a sample of Continue Reading

## Measure of Central Tendency

When we want to know averages and middle aspects of our data, we use measures of central tendency. Measures of central tendency are described with three primary functions: Mean Median Mode The mean is simply the average of a dataset. The median is the middle point of the dataset. The Continue Reading

## Common Stats Symbols

x! x! refers to a factorial of x. Meaning, that if x = 5, then x! = 5*4*3*2*1 = 120. In Python we can use the scipy library: x̄ X bar is a reference to the sample mean (as opposed to the population mean.) In Python you can calculate a Continue Reading