Learn Statistics & Biostatistics Data Analysis From Scratch

Learn fundamentals of statistics and bio statistics from very basic to upward with R-Programming (Coding Exercise)

Created by: Naeem Mahmood Ashraf
Dr Muhammad Dujana

Created by: Arslan Hamid
Bioinformatician and Data Scientist

What Will I Learn?

• Basics Concepts Related to Data and Its Types
• Different Types of Sampling Stratagies and Their Applications to Collect Data
• Installation of R and R-Studio in Operating System
• Core Functionalities of R and R-Studio & Fundamentals of R-Programming
• Installation of R-Packages and Use of Their Functions in Coding
• Core Concepts of Discriptive Statistics and Visulization of Data
• Use of R ProgrammingTo Calculation Discriptive Statistics and Data Visulization
• Concept of Probability, Types and Their Application in Daily Life
• Use of R Programming to Calculate Probabilities
• Concept of Correlation and Its Types
• Use of R Programming to Calculate Pearson, Kendalls and Spearman Correlation
• Detailed Concept of Regression and Its Types
• Use of R Programming To Build Linear and Logistic Regression
• Detailed Concept of Hypothesis Testing and Different Types of Hypothesis Tests (Z-Test, T-Test, F-Test, ANOVA, Chi-Sq))
• Use of R Programming to Calculate Different Test Statistics

Requirements

• This course is tailored for beginners, with no prerequisites required. Even if you're new to statistics and R programming, there's no need to worry. We'll start from the very basics and gradually build your understanding step-by-step, ensuring you grasp each concept clearly and can easily follow along with the content.

Target audience

• This course is for broad audiance.
• Students from basic sciences, particularly those in life sciences, will find this course especially beneficial, as it is designed to cater to their needs and enhance their understanding of R programming in scientific contexts.
• Computer science students aiming for a career in data science will greatly benefit from this course, as it provides foundational skills in R programming that are essential for data analysis and interpretation in the field.
• Sociologists who collect population data and wish to analyze and visualize it independently will find this course highly beneficial, as it equips them with the skills to effectively manage, analyze, and present data using R programming.
• Not highly recommended but economics and finance students who analyze market trends and financial data will benefit from this course, as it provides the tools to independently conduct statistical analysis and create impactful data visualizations.