Statistics - Day 3

Enrolled in Udemy's course "Statistics for Data Science and Business Analysis"

Population - Collection of ALL items of interest (N), Variable: Parameters

Sample - Subset of population (n), Variable: Statistics

• Sample should be representative of the population and random

Types of data:

1. Categorical: Yes/No, Gender etc.

2. Numerical:

• Discrete (# people, objects etc.) : integer

• Continuous (height, weight): float values

Measurement levels:

1. Qualitative

• Nominal - Rank and order doesn't matter; like gender, seasons etc.

• Ordinal - high/low/medium etc.

2. Quantitative

• Interval - doesn't have a true 0 ; like temperature (Celsius, Fahrenheit but Kelvin is Ratio)

• Ratio - has a true 0 like number of objects, distance and time

I also read about Pareto Principle: 80% of the output is given by 20%

Price's Law: 50% of the output is given by square root of the number of people doing it.

Pareto Distribution and Price's Law

Pareto Principle

Price's Law Anomaly