Day 22 of My Learning Journey: Setting Sail into Data Excellence! Today's Focus: Mathematics for Data Analysis (Stats Day 1)

STATISTICS FOR DATA ANALYTICS - 1

Material which I have taken to learn ➖
Vlearn ( Statistics) implementation in Excel .
Krish Naik ( live playlist - statistics) implementation in Python.
Paid course ( Intelliphat - Advanced in Business Analytics) implementation in Python.
Paid course ( Data Science - pw skills) implementation in Python.

Books ➖
An Introduction to Statistical Learning: With Python

Whatever I will learn in this course will be shared as per my experience.

A branch of applied mathematics that involves the collection, organising,description, presentation, analysis and interpretation of numerical data.

TYPE OF STATISTICS ➖

DESCRIPTIVE STATISTICS

INFERENTIAL STATISTICS

Descriptive statistics :- It describes the property of the dataset.

Inferential statistics :- To get results from the dataset ( it uses a dataset to get the result.)

TYPE OF DATA ➖

QUANTITATIVE DATA
QUALITATIVE DATA

LEVEL OF MEASUREMENT ( scale of measurement )

Nominal scale data.
Ordinal scale data.
Interval scale data.
Ratio scale data.

DESCRIPTIVE STATISTICS

BASIC :-
SUMMARISING
ORGANISING.

Based on Variable ➖

Univariate - Everything about that variable
One variable
Ex :- mean, median , mode.

BiVariate -
Two variable
Ex :- Scatter plot
MultiVariate -
More than One variable
Ex:- Heat map

Types of Descriptive Statistics :-

Measure of Frequency
Grouped Frequency
Ungrouped Frequency

Measure of Central Tendency
Mean, Median, Mode

Measure of Dispersion or Variation
Variance
Range,
Standard & Absolute Deviation
Coefficients of Variation

Measure of Position
Percentile & Quartile

Measure of Shape
Skewness
Kurtosis
Box & Whisker Plot

Common terms :-

Population :- complete dataset is called population.

Sample :- it is a dataset which has resemblance of the population in a small proportion which can be used for Analytics.

These functions are fundamental for various tasks in Excel, including text manipulation, logical operations, conditional formatting, and data analysis.

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Thank you for your time.