# Statistics Tests

There was a time when we only had structured data (data in form of only rows and columns). At those times, we used to do some testing on whether the observed and expected data sets having some difference between each other or not.

For example –

There are x number of people in 2012 in a city.

Now, we need to calculate for that colony what will be the number of people in 2013.

This can be done using some statistical tests which we will talk about more.

Starting from the basics –

VARIABLES – A variable is something called as column-headings on an excel sheet. It can be gender, score of a student in different subjects, age or occupation.
On the other hand OBSERVATIONS are called rows of a data that assign each of these variables a value.

There are five types of variables we will be using

1. Continuous Variable – A numerical variable that can take any value. Example(1.005, 2.55, 3.2333…….)

2. Discrete Variable – A numerical variable that can only take certain values and not like continuous variable. Example – A dice can have only 6 values. So, values between 1 to 6 keeps repeating on throwing a dice 50 times.
One more example can be GPA scored by students on 4 point scale.

3. Nominal Variable – A categorical variable just like gender. This variable will have 2 or more unordered categories.
Example – Blood Group, States of a country.

4. Ordinal Variable –  A categorical variable that has 2 or more categories having an order.
Example – Occupation ranking like Associate then Senior Associate …… Department Manager.

Check out some of the tests performed using these variables –

1. CHI-SQUARE TEST – CONTINGENCY TABLE

2. CHI-SQUARE TEST – GOODNESS OF FIT

3. ONE SAMPLE T TEST

4. TWO SAMPLE T TEST

5. ANOVA – ANALYSIS OF VARIANCE

6. ANCOVA – ANALYSIS OF CO-VARIANCE

7. MANOVA – MULTIVARIATE ANALYSIS OF VARIANCE