- Statistics for Beginners
- Free tutorial
- Rating: 4.3 out of 54.3 (179 ratings)
- 4,289 students
- 1hr 59min of on-demand video
- Created by DataMites Solutions
- English
What you’ll learn
- Understand Statistics Basics
- Statistics – Data Types and Application
- Harnessing Data – Sampling Techniques
- Exploratory Data Analysis
Requirements
- Basic Mathematical knowledge is preferred.
Description
Data Science is an inter disciplinary fields combining Statistics, Programming, Machine Learning and Business Knowledge.
Statistics is the key field in analyzing the data to extract insights for business decisions. Though, Statistics as a field is vast, a limited concepts involving quantitative methods are useful in data science.
The science of collecting, describing, and interpreting data is popularly known as Statistical leveraging in Data Science
Two areas of Statistics in Data Science:
Descriptive statistics – Methods of organizing, summarizing, and presenting data in an informative way
Inferential statistics – The methods used to determine something about a population on the basis of a sample
A strong statistics foundation is mandatory for data science professionals, as statistics is basis for any data analysis.
Statistics is also predominantly used in Machine Learning for feature engineering.
————————-
This is an introductory course on Statistics for Data Science for Beginners.
There are no hard prerequisites for this course. Anyone interested can pursue.
The goal of this course is to provide a statistics with simple examples and learning the learners to get comfortable with Statistics as they move on to more advanced statistical methods.
Curriculum
INTRODUCTION
1. Statistics Overview – Introduction
2. Statistics Basic Terminology
3. Types of Data
HARNESSING DATA
1. Introduction – Sampling Methods
2. Sampling Methods
3. Cluster Sampling
4. Systematic Sampling
5. Biased Sampling
6. Sampling Error
EXPLORATORY DATA ANALYSIS
1. EDA – Central Tendencies
2. EDA – Variability
3. EDA – Histogram, Z-Value, Normal Distribution
Happy Learning
Team DataMites
Who this course is for:
- Data Science Aspirants, who want to get good foundation of Statistics
Show less
Course content
3 sections • 12 lectures • 1h 59m total lengthCollapse all sections
Introduction3 lectures • 36min
- Statistics Overview – Introduction02:22
- Statistics Basic Terminology13:10
- Types of Data20:28
Harnessing Data6 lectures • 28min
- Introduction – Sampling Methods07:23
- Sampling Methods07:08
- Cluster Sampling02:06
- Systematic Sampling05:57
- Biased Sampling03:39
- Sampling Error01:39
Exploratory Data Analysis (EDA)3 lectures • 56min
- EDA – Central Tendencies16:45
- EDA – Variability16:25
- EDA – Histogram, Z-Value, Normal Distribution22:22
