[100% Off] Statistics Simplified: A Step - By - Step Guide

Learn Statistics From Basic to Advance Techniques

Added on September 8, 2025 Teaching & Academics 2 min read

What you’ll learn

Introduction to Statistics
What is the type of Statistics
Importance of Statistics
Measure of Central Tendency
Advantages and Disadvantages of Mean ,Median
and Mode
Conversion of Ungrouped data to Grouped data
Measure of Dispersion
Data visualization
Basic concepts of Probability
Properties of Probability
Introduction to Conditional Probability
Introduction to Bayes Theorem
Introduction to Random Variable
Introduction to Mathematical Expectation
Introduction to Distributions
Introduction to Sampling Distribution
Introduction to Central Limit Theorem
Introduction to Estimation and Confidence Interval
Hypothesis Testing
Concept of Linear Regression and Correlation Coefficient
Introduction to Experimental Design(ANOVA)

Requirements

Idea of Basic Mathematics
Laptop Computer/Smart Phone with Internet connection
No programming Required
Willingness and zeal to learn new things

Description

Statistics Course Description

This course provides a comprehensive introduction to statistics, covering fundamental concepts and techniques. Students will learn to collect, analyze, and interpret data to make informed decisions.

What are Statistics? Definition, importance, and application of statistics.

Types of Statistics: Descriptive and inferential Statistics.

Types of data: qualitative and quantitative data, level of measurement (Nominal, Ordinal, Interval, and Ratio).

v Ungrouped vs Grouped data: Differences and applications.

Measure of central tendency: Mean, median, Mode.

Measure of dispersion: Range, Variance, Standard Deviation, Mean Deviation

Introduction to probability: Basic concepts, Rules, and applications.

Introduction to Distribution: Normal distribution, Binomial distribution and Poisson distribution.

Introduction to sampling distribution: Concepts, importance, and applications.

Random variable, discrete and continuous random variables.

Hypothesis testing, Types of error, Types of hypotheses.

Experimental Design (ANOVA): Principles, types and applications.

Linear Regression and correlation coefficient: Simple linear Regression, correlation coefficient and interpretation.

Key Take away :

Under Statistical concepts and techniques

Collect, analyze, and interpret data.

Apply statistical methods to real-world problems.

Make informed decision based on data analysis,

Course Objectives:

Develop statistical literacy and critical thinking skills.

Apply statistical techniques to solve problems.

v Interpret and communicate statistical results effectively.

This course provides a solid foundation in statistics, preparing students for further study, enhanced researchers to understand the concepts of statistics as well as academician, for practical applications in various fields.