"Day 23 of My Learning Journey: Setting Sail into Data Excellence! ⛵️ Today's Focus: Maths for Data Analysis (Stats Day -2)

STATISTICS FOR DATA ANALYTICS - 1

Type of Data :-

Qualitative & Quantitative

Qualitative ( categorical data)
a. Nominal ( no ranking of data )
Eg :- Gender, Blood Group
b. Ordinal ( ranking of data )
Eg :- Good, bad, very bad

Quantitative ( numerical value )
Discrete
Eg :- no. of children
Continuous
Eg :- weight, height.

Scale of Measurement :-
Nominal Scale Data
Ordinal Scale Data
Interval Scale Data
Ratio Scale Data

Nominal Scale data
Qualitative / categorical
Order does not matter.

Eg :- Gender, colour.

Ordinal Scale data
Ranking and order is important
Difference cannot be measure

Eg : - rating ( 2- good , 1- best, 3- bad)

Interval Scale Data
Order matter
Difference can be measured
Ratio cannot be measured
No True “0” starting point.

Eg:- temperature variable ( kelvin and celsius and fahrenheit ), value can go to negative.

Ratio Scale Data
Order matter
Difference are measurable
Ratio can be calculated
“0” starting can’t be negative.

Eg :- student marks in a class.

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