Module 1: Getting started with statistics

Fundamentals of statistics

We have two types of statistics:

Descriptive : it describes the properties of a sample and population through visualization
Inferential Stats : it helps make predictions or conclusion about a larger group based on sample. In order terms, it helps generalize from sample to larger group.

Key differences

Feature	Descriptive Statistics	Inferential Statistics
Purpose	Describes & summarizes data	Makes predictions about a population
Based on	The entire dataset	A sample of data
Example	“The average height of students in my class is 1.7m.”	“Based on 30 students, the average height of all students in school is 1.7m.”
Uses	Charts, averages, percentages	Probability, hypothesis testing

Steps to start in statistics:

Collection of data
Organization of data
Presentation of data
Analysis of data
Interpretation of data

Module 2 : Descriptive Statistics

Basics of Descriptive Statistics

Descriptive statistics is about to summarize and organize data of the same group through certain number.

It helps to quickly understand trends, make better decisions and summarize a large datasets in a simple way.

Unlike the inferential statistics, descriptive stats do not predict or infer anything about the future. It’s a tool that help organize and summarize existing data in a clear way.

There are different types of descriptive statistic:

Measure of central Tendency :
- Mean (Average)
- Median (Middle value). It requires data to be sorted
- Mode (Most frequent value)
Measure of Spread / Measure of variability
- Range : [Highest - Lowest]
- Standard deviation : Tells if the data are fluctuating or consistent
- Variance
Data Visualization
- Bar Charts tables

Measure of Central Tendency

Mean (AVERAGE)