Description
This course provides a comprehensive introduction to the fundamental
concepts of statistics, equipping students with the tools necessary to
analyze and interpret data effectively. This course lays a strong
foundation for advanced studies and professional applications in fields
such as data science, data analyst, data engineering, AI and Machine
Learning, business analytics, and research.
Learning Outcomes
- Understanding Fundamental Concepts of Statistics and data
processing - Applying Analytical Techniques
- Improving problem solving skills utilizing statistical methods.
Target Group
- Undergraduate Students who need a strong foundation in statistics.
- Learners entering advanced studies in data science, research, or
analytics who require a refresher or deeper understanding of
statistical concepts - Beginners aiming to enter data-centric roles such as data science,
data analyst, data engineering, AI and Machine Learning, business analytics, and research and requiring essential knowledge of
statistical methods.
Prerequisites
- Interest in Data , Data Processing and Data Analysis
Duration
- 20hrs (Sunday only)
- 12:30 PM to 2:30 PM
Modules
Course Outlines
What is statistics?- Descriptive and Inferential Statistics Variables and Types of Data, Data Collection and Sampling Techniques
- Random Sampling
- Systematic Sampling
- Stratified Sampling
- Cluster Sampling
- Frequency Distributions and Graphs
- Data Description
- Measures of Central Tendency
- Measures of Variation
- Measures of Position
- Confidence Intervals and Sample Size
- Hypothesis Testing
- Correlation and Regression
